CN114819506A - Online intelligent management and control platform and method for roadbed layered compaction quality - Google Patents
Online intelligent management and control platform and method for roadbed layered compaction quality Download PDFInfo
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Abstract
The invention discloses a roadbed layered compaction quality online intelligent control platform and a roadbed layered compaction quality online intelligent control method. The platform comprises intelligent front-end acquisition equipment, a quality monitoring platform and a user terminal. The intelligent front-end acquisition equipment consists of: the device comprises a portable dynamic resilience modulus instrument, a road roller and a soil moisture content tester, and is used for collecting field data, positioning a measuring point and wirelessly transmitting the data to a quality monitoring platform; the quality monitoring platform excavates and analyzes the acquired data, the site measuring point data is displayed in a chart or curve form, the site monitoring data is associated with the layer-by-layer built three-dimensional model, and a user can click the measuring point, the chart to display detailed information, historical monitoring data and a measuring point moving path; the user terminal can send instructions to field monitoring personnel, trace the source of roadbed compaction quality reasons and guide a construction field to process abnormal conditions. The construction quality of the roadbed in the construction site can be effectively controlled.
Description
Technical Field
The invention relates to the technical field of construction process quality monitoring, in particular to a roadbed layered compaction quality online intelligent control platform and a roadbed layered compaction quality online intelligent control method based on multipoint synchronous dynamic rebound detection.
Background
Typically, the quality of subgrade compaction is checked and evaluated based on pit sampling during the check, which may damage the integrity of the pavement. Meanwhile, the inspection method can interfere with the construction operation of the working face on one hand, and on the other hand, the construction progress is influenced because the experimental result cannot be obtained quickly, and the real-time feedback of the compaction quality is difficult to realize.
The portable dynamic resilience modulus tester shows that the tester has strong practicability after being tested in the market and each construction site. Aiming at road beds filled with soil, stone and soil-stone, a rapid detection method for the compaction quality of the road beds is provided.
With the continuous development of information technology, particularly Internet of things technology and equipment intelligent technology, the digital technology is combined with the traditional measurement means, is a new trend of civil engineering detection technology development, and a roadbed quality intelligent control platform is constructed by necessarily combining highway construction and inspection characteristics and early-stage research foundation, so that the method has important practical significance for ensuring roadbed construction quality and realizing real-time evaluation and timely feedback of construction quality.
Disclosure of Invention
The invention provides an intelligent control platform for the layered compaction quality of a roadbed based on multipoint synchronous dynamic rebound detection, which aims to solve the problem of accurate control of the compaction quality in the roadbed construction process.
In order to achieve the above purpose, the specific technical scheme of the invention is as follows:
an online intelligent management and control platform for roadbed layered compaction quality comprises intelligent front-end acquisition equipment, a quality monitoring platform and a user terminal;
the intelligent front-end acquisition equipment acquires dynamic resilience modulus, compactness and water content data of the on-site measuring points and positioning data of the measuring points, and wirelessly transmits various data to the quality monitoring platform;
the quality monitoring platform comprises:
the data analysis decision module is used for mining, analyzing and processing various acquired data, including data noise reduction, function comparison analysis and graph display of field measuring point data, and judging the qualification rate of the dynamic resilience modulus;
the roadbed compaction early warning module is connected with the data analysis decision module, and is used for early warning the abnormal data of the region and tracing the source of the early warning reason;
the three-dimensional module is used for acquiring various data and field pictures acquired by the intelligent front-end acquisition equipment to build a three-dimensional model layer by layer, associating field measurement point data with the three-dimensional model, and checking detailed chart display information, historical monitoring data and measurement point moving paths by clicking a measurement point by a user;
and the user terminal is used for inquiring data information of the site monitoring point, sending an instruction to site personnel, tracing the source of the roadbed compaction quality reason and guiding the construction site to process abnormal conditions.
Further, in the technical scheme of the invention: the intelligent front-end acquisition equipment is used for acquiring various types of data information of the roadbed, and the database system comprises a roadbed dynamic resilience modulus unqualified reason database and a disposal countermeasure database.
Further, the intelligence front end collection equipment includes: portable dynamic resilience modulus appearance, road roller sensor, soil moisture content apparatus.
Furthermore, the intelligent front-end acquisition equipment further comprises a positioning chip and a data transmission module, and the positioning chip and the data transmission module are used for accurately positioning the monitoring measuring points and transmitting the positioning data of the measuring points.
Furthermore, the user terminal comprises a remote monitoring PC terminal and a mobile webpage terminal, wherein the mobile webpage terminal comprises a user registration/login port, a user permission setting port and a data viewing/downloading port.
Further, the quality intelligent management and control platform further comprises a reserved related expansion function web port.
Further, in the technical scheme of the invention: the quality monitoring platform further comprises a data capturing module, and local meteorological hydrographic data are captured from a network in real time through wireless network communication.
Another objective of the present invention is to provide an intelligent control method for roadbed layered compaction quality based on multipoint synchronous dynamic springback detection, including the following steps:
1) selecting a typical test section as a data calibration section, collecting dynamic resilience modulus, compactness and water content data of a field measuring point and positioning data of the measuring point by using intelligent front-end collecting equipment, and wirelessly transmitting various data to a quality monitoring platform;
verifying the relation among the dynamic resilience modulus, the compactness and the water content by adopting a multivariate regression model, establishing a relation chart between the dynamic resilience modulus and the compactness, and between the compactness and the water content, and displaying the relation chart on a display interface of a quality monitoring platform;
2) the quality monitoring platform receives and stores various data from the measuring points, the obtained data is subjected to distance checking calculation through a K-MEANS clustering algorithm, noise point data are removed, corresponding dynamic resilience modulus values under different compactnesses are obtained, the data are mined and called, and the dynamic resilience modulus value corresponding to the specified roadbed compactedness is selected as a standard value;
3) the data analysis decision module compares the measured values and the calculated representative values with the standard values, and judges the qualification rate of the dynamic resilience modulus of the roadbed according to the comparison result;
4) the roadbed compaction early warning module sets three levels of early warnings, compares early warning threshold values of different levels with measured values or calculation representative values of roadbed dynamic resilience modulus, and starts a corresponding early warning mechanism according to comparison results:
the first-stage early warning and the second-stage early warning are measured values, the first-stage early warning threshold value is set to be 95% of the standard value, and the second-stage early warning threshold value is set to be 85% of the standard value; calculating representative value early warning in the third stage, and setting a threshold value of the early warning in the third stage as a standard value; when the measured value is lower than the early warning threshold value or the evaluation road section calculation representative value is smaller than the standard value, an alarm mechanism is started, and information is reported to each management layer of the project for early warning;
5) establishing a complete roadbed three-dimensional model according to the position information of the site positioning base station and the three-dimensional position information acquired by the intelligent front-end acquisition equipment, importing a design model in advance, establishing the design model according to a design drawing, acquiring site three-dimensional coordinates, mainly acquiring the site three-dimensional coordinates through the positioning base station and the monitoring equipment, increasing the site three-dimensional model layer by layer along with a compaction layer, displaying relevant information of measuring points on the surface of the compaction layer of the site three-dimensional model, and calculating the site earth and stone square quantity through section integration;
6) associating data information of compactness, water content, a road roller and dynamic resilience modulus of a measuring point with a field three-dimensional model, displaying measuring point data in the three-dimensional model in real time through measuring point information and position time information acquired by intelligent front-end acquisition equipment, and generating a measuring point moving track and historical monitoring data query through measuring point position information and time display;
7) establishing a roadbed dynamic resilience modulus unqualified reason database and a disposal strategy database, wherein when primary or secondary early warning occurs, field detection personnel need to analyze reasons and select to input, and if the reasons are the reasons of equipment operation errors or the test surface is not well-arranged, the detection point can be re-detected to cover the original detection result; when early warning occurs, each management layer of the project selects a disposal strategy according to the authority level;
8) and users with different authorities input, edit and modify the basic information of the operation process, and different authority management users inquire the data information of the on-site monitoring point through the user terminal, send instructions to on-site personnel and inform related responsible persons of the early warning information.
Further, the qualification rate of the dynamic resilience modulus of the roadbed in the step 3) is judged:
when the calculation representative value is greater than or equal to the standard value and all the dynamic rebound moduli of the single-point roadbed are greater than or equal to 95% of the standard value, the qualification rate of the roadbed dynamic rebound modulus of the evaluation road section is 100%; when the calculation representative value is more than or equal to the standard value and the dynamic resilience modulus of the single-point roadbed is all more than or equal to 85% and less than 95% of the standard value, calculating the qualified rate according to the number of the measuring points; and when the calculated representative value is smaller than the standard value or the dynamic resilience modulus of a single-point roadbed is smaller than 85% of the standard value, the dynamic resilience modulus of the roadbed of the evaluated road section is unqualified, and the corresponding project is unqualified.
Further, in step 6), the compacted layer surface of the on-site three-dimensional model shows: measuring point positions, measuring point moving tracks, starting point pile numbers, stop point pile numbers, left and right amplitudes, traveling directions and compaction layer numbers; and (4) establishing a cross-sectional diagram through three-dimensional model identification on the measuring point related information interface, and clicking the specific layer number of the three-dimensional model to display the historical detection data of the corresponding rolling layer.
Compared with the prior art, the invention has the beneficial effects that:
the roadbed layering compaction quality intelligent control platform monitors dynamic resilience modulus, compaction degree and water content of a plurality of measuring point positions in the roadbed compaction process, analyzes the relevance among measuring point data, displays the measured point data in a relevance curve form, is more visual, checks the chart information, historical monitoring data, moving path and other information of each measuring point data of a compaction layer by using a field three-dimensional model, judges the qualification rate according to the standard value of the roadbed resilience module, performs grading early warning according to the measured value and the comparison result of the calculation and the early warning threshold value, provides accurate and efficient quality control means in the roadbed construction process for all levels of project managers and constructors, and further provides basic data for design index verification, staged project communication acceptance and later management and maintenance units.
A Web port with related expansion functions is reserved on the roadbed quality intelligent control platform, and a premise is provided for adding and realizing subsequent functions, such as basic detection items of deflection values, flatness and the like and embedding of a complex on-site three-dimensional model. By adopting the platform, one-sidedness, randomness and data delay of post spot inspection can be effectively avoided, and a new method is provided for real-time monitoring of the compaction quality of the highway subgrade
Drawings
FIG. 1 is a structural framework of an intelligent management and control platform for roadbed layered compaction quality based on multipoint synchronous dynamic rebound detection;
fig. 2 is a technical architecture of the roadbed layered compaction quality intelligent control platform.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present invention, are given by way of illustration and explanation only, not limitation.
Example 1
A roadbed layered compaction quality intelligent control platform based on multipoint synchronous dynamic springback detection is mainly composed of an intelligent front-end acquisition device, a quality monitoring platform and a user terminal, as shown in figure 1. Wherein:
the intelligent front-end acquisition equipment consists of: the device is characterized by comprising a portable dynamic rebound modulus instrument, a road roller sensor and a soil moisture content tester which are integrated with data acquisition, positioning and transmission into a whole, and is used for acquiring field data, positioning a measuring point and wirelessly transmitting the data to a quality monitoring platform.
The quality monitoring platform excavates and analyzes the acquired data, and the data is subjected to noise reduction, function comparison analysis, regional data abnormity early warning, early warning reason tracing and the like, the data of the on-site measuring points are displayed in a graph and curve form, the on-site monitoring data is associated with the layer-by-layer built three-dimensional model, and a user can click the measuring points, the graph displays detailed information, historical monitoring data and a measuring point moving path.
The data analysis decision module is used for mining, analyzing and processing various acquired data, including data noise reduction, function comparison analysis and graph display of field measuring point data, and judging the qualification rate of the dynamic resilience modulus;
and the roadbed compaction early warning module is connected with the data analysis decision module, and is used for early warning the abnormal data in the region and tracing the source of the early warning reason.
And the three-dimensional module is used for acquiring various data and field pictures acquired by the intelligent front-end acquisition equipment to construct a three-dimensional model layer by layer, associating field measurement point data with the three-dimensional model, and checking detailed chart display information, historical monitoring data and measurement point moving paths by clicking a measurement point by a user.
The user terminal checks the information displayed on the platform at the Web end, different users correspond to different management authorities, and the user terminal can send instructions to field monitoring personnel, trace the source of the roadbed compaction quality reasons and guide a construction field to process abnormal conditions.
The intelligent front-end acquisition device in the above platform should include: dynamic modulus of resilience measuring sensor, location chip, data transmission module are supplementary carries out accurate location to detecting the measurement station with the location basic station, and the space orientation precision is more than the centimetre level. The measuring point position of the roadbed compaction quality of the construction site can be accurately positioned.
In one embodiment, the functions implemented by the quality monitoring platform of the above platform include: and receiving various types of data from the intelligent front-end acquisition equipment, storing the data in a database platform, mining and calling the data through algorithms such as a KD decision tree and removing noise data, verifying whether the dynamic resilience modulus in the obtained monitoring data is in an actually set threshold range or not, and judging whether the dynamic resilience modulus meets the requirements or not. And generating a curve and an icon by the platform to display the dynamic resilience modulus data condition in the actual construction process.
The method specifically comprises the steps of project and relevant information in a mark section, meteorological hydrological information in a construction area, and a quality intelligent control platform, wherein a relevant expansion function web port is reserved, so that a foundation is laid for adding and realizing subsequent functions, such as deflection values, flatness and other basic detection items.
The user terminal in the platform is displayed with the user in a Web page form, and different users have different permissions including functions of creating, accessing, editing and the like.
Example 2
A roadbed layered compaction quality intelligent control method based on multipoint synchronous dynamic rebound detection comprises the following steps:
1) selecting a typical test section as a data calibration section, collecting dynamic resilience modulus, compactness and water content data of a field measuring point and positioning data of the measuring point by using intelligent front-end collecting equipment, and wirelessly transmitting various data to a quality monitoring platform;
verifying the relation among the dynamic resilience modulus, the compactness and the water content by adopting a multivariate regression model, establishing a relation chart between the dynamic resilience modulus and the compactness, and between the compactness and the water content, and displaying the relation chart on a display interface of a quality monitoring platform;
2) the quality monitoring platform receives and stores various data from the measuring points, the obtained data is subjected to distance checking calculation through a K-MEANS clustering algorithm, noise point data are removed, corresponding dynamic resilience modulus values under different compactnesses are obtained, the data are mined and called, and the dynamic resilience modulus value corresponding to the specified roadbed compactedness is selected as a standard value;
3) and the data analysis decision module compares the measured values and the calculation representative values with the standard values, and judges the qualification rate of the dynamic resilience modulus of the roadbed according to the comparison result: when the calculation representative value is greater than or equal to the standard value and all the dynamic rebound moduli of the single-point roadbed are greater than or equal to 95% of the standard value, the qualification rate of the roadbed dynamic rebound modulus of the evaluation road section is 100%; when the calculation representative value is more than or equal to the standard value and the dynamic resilience modulus of the single-point roadbed is all more than or equal to 85% and less than 95% of the standard value, calculating the qualification rate according to the number of the measuring points; and when the calculated representative value is smaller than the standard value or the dynamic resilience modulus of a single-point roadbed is smaller than 85% of the standard value, the dynamic resilience modulus of the roadbed of the evaluated road section is unqualified, and the corresponding project is unqualified.
4) The roadbed compaction early warning module sets up tertiary early warning, compares different grades of early warning threshold value and roadbed dynamic resilience modulus's measured value and calculation representative value, opens corresponding early warning mechanism according to the comparison result:
the first-stage early warning and the second-stage early warning are measured values, the first-stage early warning threshold value is set to be 95% of the standard value, and the second-stage early warning threshold value is set to be 85% of the standard value; calculating representative value early warning in the third stage, and setting a threshold value of the early warning in the third stage as a standard value; when the measured value is lower than the early warning threshold value or the evaluation road section calculation representative value is smaller than the standard value, an alarm mechanism is started, and information is reported to each management layer of the project for early warning;
the early warning of the current stage is the early warning of the representative value after data processing, the representative value is calculated according to all measured values in the road section, and the early warning of the current stage is judged to be unqualified as long as the representative value is lower than the standard value!
5) Establishing a complete roadbed three-dimensional model according to the position information of the site positioning base station and the three-dimensional position information acquired by the intelligent front-end acquisition equipment, importing a design model in advance, establishing the design model according to a design drawing, acquiring site three-dimensional coordinates, mainly acquiring the site three-dimensional coordinates through the positioning base station and the monitoring equipment, increasing the site three-dimensional model layer by layer along with a compaction layer, displaying relevant information of measuring points on the surface of the compaction layer of the site three-dimensional model, and calculating the site earth and stone square quantity through section integration;
specifically, the quality monitoring platform can perform layer-by-layer three-dimensional modeling on the compaction process of a construction site, perform elevation measurement on the surface after the steps of clearing the surface by a bulldozer, leveling by a leveler and the like to generate a basic model, on the basis, the roadbed compaction layer model gradually increases along with the rolling construction height and finally approaches the design model, and in the process of forming the site three-dimensional model, the site earth and stone volume is calculated through section integration. The field models are mainly divided into two categories: and (4) filling the typical embankment, dredging and backfilling the embankment model. In the two models, the field dynamic BIM model gradually approaches to the design of the three-dimensional BIM model along with the increase of the compacted layer.
On-site three-dimensional model compacted layer surface display: measuring point position, measuring point moving track, starting point pile number, stop point pile number, left and right width, traveling direction and compaction layer number (the second compaction layer). Measuring point related information content: detecting specific time, detecting personnel, operation sections, pile numbers and positions, dynamic resilience modulus values, corresponding converted compaction degree, compaction degree control values, qualification or not, equipment ID, water content, compaction times and compaction equipment parameters. And (4) establishing a cross-sectional diagram through three-dimensional model identification on the measuring point related information interface, and clicking the specific layer number of the three-dimensional model to display the historical detection data of the corresponding rolling layer.
6) Associating data information of compactness, water content, a road roller and dynamic resilience modulus of a measuring point with a field three-dimensional model, displaying measuring point data in the three-dimensional model in real time through measuring point information and position time information acquired by intelligent front-end acquisition equipment, and generating a measuring point moving track and historical monitoring data query through measuring point position information and time display;
7) establishing a roadbed dynamic resilience modulus unqualified reason database and a disposal strategy database, wherein when primary or secondary early warning occurs, field detection personnel need to analyze reasons and select to input, and if the reasons are the reasons of equipment operation errors or the test surface is not well-arranged, the detection point can be re-detected to cover the original detection result; when early warning occurs, each management layer of the project selects a disposal strategy according to the authority level;
8) and users with different authorities input, edit and modify the basic information of the operation process, and different authority management users inquire the data information of the on-site monitoring point through the user terminal, send instructions to on-site personnel and inform related responsible persons of the early warning information.
Specifically, the quality monitoring platform represents the detection condition of the on-site roadbed compaction quality in the shapes of red, yellow and green. All or part of the section roadbed compaction quality detection reports of the project can be downloaded in a one-key mode according to needs at different project management levels, and the reports can not be changed.
In one embodiment, the user terminal in the platform can input basic information of a project and field information on the intelligent monitoring platform, and users with different authorities can input, edit and modify the basic information of each operation field.
The platform is adopted to provide accurate and efficient quality control means for managers and constructors at all levels of projects in the roadbed construction process, and further provide basic data for design index verification, stage project delivery acceptance and later management and maintenance units.
By adopting the platform, one-sidedness, randomness and successfulness of post spot inspection can be effectively avoided, and a new method is provided for real-time monitoring of the compaction quality of the highway subgrade. The method provides accurate and efficient quality control means in the roadbed construction process for managers and constructors at all levels of projects, and further provides basic data for design index verification, periodic project acceptance and later management and maintenance units.
Although the embodiments of this patent have been disclosed above, they are not limited to the applications listed in the specification and the examples, which are fully applicable to many areas of applicability of this patent, and additional modifications will readily occur to those skilled in the art. The invention is therefore not to be limited to the specific details and illustrations shown and described herein, without departing from the general concept defined by the claims and their equivalents.
Claims (10)
1. An online intelligent management and control platform for roadbed layered compaction quality, which comprises an intelligent front-end acquisition device, a quality monitoring platform and a user terminal, and is characterized in that,
the intelligent front-end acquisition equipment acquires dynamic resilience modulus, compactness and water content data of the on-site measuring points and positioning data of the measuring points, and wirelessly transmits various data to the quality monitoring platform;
the quality monitoring platform comprises:
the data analysis decision module is used for mining, analyzing and processing various acquired data, including data noise reduction, function comparison analysis and graph display of field measuring point data, and judging the qualification rate of the dynamic resilience modulus;
the roadbed compaction early warning module is connected with the data analysis decision module, and is used for early warning the abnormal data of the region and tracing the source of the early warning reason;
the three-dimensional module is used for acquiring various data and field pictures acquired by the intelligent front-end acquisition equipment to build a three-dimensional model layer by layer, associating field measurement point data with the three-dimensional model, and checking detailed chart display information, historical monitoring data and measurement point moving paths by clicking a measurement point by a user;
and the user terminal is used for inquiring data information of the site monitoring point, sending an instruction to site personnel, tracing the source of the roadbed compaction quality reason and guiding the construction site to process abnormal conditions.
2. The online intelligent management and control platform for the layered compaction quality of the roadbed according to claim 1, further comprising a database system for storing various types of data information from the intelligent front-end acquisition equipment, wherein the database system comprises a roadbed dynamic resilience modulus disqualification reason database and a disposal countermeasure database.
3. The online intelligent management and control platform for the roadbed layered compaction quality as recited in claim 1, wherein the intelligent front-end acquisition equipment comprises: portable dynamic resilience modulus appearance, road roller sensor, soil moisture content apparatus.
4. The online intelligent management and control platform for the roadbed layered compaction quality as claimed in claim 3, wherein the intelligent front-end acquisition equipment further comprises a positioning chip and a data transmission module, and the positioning chip and the data transmission module are used for accurately positioning the monitoring measuring points and transmitting positioning data of the measuring points.
5. The online intelligent management and control platform for the roadbed layered compaction quality as claimed in claim 1, wherein the user terminal comprises a remote monitoring PC terminal and a mobile webpage terminal, and the mobile webpage terminal comprises a user registration/login port, a user permission setting port and a data viewing/downloading port.
6. The online intelligent management and control platform for the roadbed layered compaction quality as recited in claim 1, wherein the intelligent management and control platform for the roadbed quality further comprises a reserved related extended function web port.
7. The online intelligent management and control platform for the roadbed layered compaction quality as claimed in claim 1, wherein the quality monitoring platform further comprises a data capture module for capturing local meteorological hydrological data from a network in real time through wireless network communication.
8. The online intelligent management and control method for the layered compaction quality of the roadbed is characterized by comprising the following steps of:
1) selecting a typical test section as a data calibration section, collecting dynamic resilience modulus, compactness and water content data of a field measuring point and positioning data of the measuring point by using intelligent front-end collecting equipment, and wirelessly transmitting various data to a quality monitoring platform;
verifying the relation among the dynamic resilience modulus, the compactness and the water content by adopting a multivariate regression model, establishing a relation chart between the dynamic resilience modulus and the compactness, and between the compactness and the water content, and displaying the relation chart on a display interface of a quality monitoring platform;
2) the quality monitoring platform receives and stores various data from the measuring points, the obtained data is subjected to distance checking calculation through a K-MEANS clustering algorithm, noise point data are removed, corresponding dynamic resilience modulus values under different compactnesses are obtained, the data are mined and called, and the dynamic resilience modulus value corresponding to the specified roadbed compactedness is selected as a standard value;
3) the data analysis decision module compares the measured values and the calculated representative values with the standard values, and judges the qualification rate of the dynamic resilience modulus of the roadbed according to the comparison result;
4) the roadbed compaction early warning module sets three levels of early warnings, compares early warning threshold values of different levels with measured values or calculation representative values of roadbed dynamic resilience modulus, and starts a corresponding early warning mechanism according to comparison results:
the first-stage early warning and the second-stage early warning are measured values, the first-stage early warning threshold value is set to be 95% of the standard value, and the second-stage early warning threshold value is set to be 85% of the standard value; calculating representative value early warning in the third stage, and setting a threshold value of the early warning in the third stage as a standard value; when the measured value is lower than the early warning threshold value or the evaluation road section calculation representative value is smaller than the standard value, an alarm mechanism is started, and information is reported to each management layer of the project for early warning;
5) establishing a complete roadbed three-dimensional model according to the position information of the site positioning base station and the three-dimensional position information acquired by the intelligent front-end acquisition equipment, importing a design model in advance, establishing the design model according to a design drawing, acquiring site three-dimensional coordinates, mainly acquiring the site three-dimensional coordinates through the positioning base station and the monitoring equipment, increasing the site three-dimensional model layer by layer along with a compaction layer, displaying relevant information of measuring points on the surface of the compaction layer of the site three-dimensional model, and calculating the site earth and stone square quantity through section integration;
6) associating data information of compactness, water content, a road roller and dynamic resilience modulus of a measuring point with a field three-dimensional model, displaying measuring point data in the three-dimensional model in real time through measuring point information and position time information acquired by intelligent front-end acquisition equipment, and generating a measuring point moving track and historical monitoring data query through measuring point position information and time display;
7) establishing a roadbed dynamic resilience modulus unqualified reason database and a disposal strategy database, wherein when primary or secondary early warning occurs, field detection personnel need to analyze reasons and select to input, and if the reasons are the reasons of equipment operation errors or the test surface is not well-arranged, the detection point can be re-detected to cover the original detection result; when early warning occurs, each management layer of the project selects a disposal strategy according to the authority level;
8) and users with different authorities input, edit and modify the basic information of the operation process, and different authority management users inquire the data information of the on-site monitoring point through the user terminal, send instructions to on-site personnel and inform related responsible persons of the early warning information.
9. The online intelligent management and control method for the layered compaction quality of the roadbed according to claim 8, wherein the qualification rate of the dynamic resilience modulus of the roadbed in the step 3) is determined as follows:
when the calculation representative value is greater than or equal to the standard value and all the dynamic rebound moduli of the single-point roadbed are greater than or equal to 95% of the standard value, the qualification rate of the roadbed dynamic rebound modulus of the evaluation road section is 100%; when the calculation representative value is more than or equal to the standard value and the dynamic resilience modulus of the single-point roadbed is all more than or equal to 85% and less than 95% of the standard value, calculating the qualification rate according to the number of the measuring points; and when the calculated representative value is smaller than the standard value or the dynamic resilience modulus of a single-point roadbed is smaller than 85% of the standard value, the dynamic resilience modulus of the roadbed of the evaluated road section is unqualified, and the corresponding project is unqualified.
10. The online intelligent management and control method for the roadbed layered compaction quality as claimed in claim 8, wherein in the step 6), the compacted layer surface of the on-site three-dimensional model displays: measuring point positions, measuring point moving tracks, starting point pile numbers, stop point pile numbers, left and right amplitudes, traveling directions and compaction layer numbers; and (4) establishing a cross-sectional diagram through three-dimensional model identification on the measuring point related information interface, and clicking the specific layer number of the three-dimensional model to display the historical detection data of the corresponding rolling layer.
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