CN112883087A - Dam intelligent grouting and engineering geological big data visual analysis method - Google Patents
Dam intelligent grouting and engineering geological big data visual analysis method Download PDFInfo
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- 238000007689 inspection Methods 0.000 claims abstract description 21
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- 239000004568 cement Substances 0.000 description 1
- 238000009430 construction management Methods 0.000 description 1
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Abstract
A dam intelligent grouting and engineering geological big data visualization analysis method comprises the following steps of performing metadata standard management: the method is used for managing the format, quality, scale, acquisition frequency and transmission frequency of dam grouting survey data, design data, construction data, result data and quality inspection data; and (3) metadata collection management: the method is used for collecting, interacting and storing dam grouting survey data, design data, construction data, result data and quality inspection data; and (3) performing metadata quality management: the intelligent grouting construction data management system is used for managing the quality of intelligent grouting construction data, achievement data and quality inspection data, and comprises the steps of data quality index planning, data quality analysis, data problem statistics, data problem form generation and the like; the invention aims to further ensure the grouting quality and provide guarantee for realizing intellectualization of a grouting process, and provides an intelligent grouting data acquisition, visualization and depth analysis method.
Description
Technical Field
The invention relates to a dam intelligent grouting and engineering geological big data visualization analysis method, and belongs to the field of hydraulic structure engineering.
Background
The grouting technology is an effective measure for reinforcing the hydraulic dam, and plays a positive promoting role in the construction of the hydraulic dam. The grouting mainly comprises two types, namely consolidation grouting and curtain grouting. Wherein, the consolidation grouting is to utilize a drill hole to press high-grade cement slurry or chemical slurry into a rock body so as to seal a crack, strengthen the integrity of bedrock and achieve the aim of improving the strength and the rigidity of the rock body; the curtain grouting is to fill grout into cracks and pores of rock mass or soil layer to form a continuous waterproof curtain to reduce seepage flow and osmotic pressure, thereby reducing and controlling osmotic pressure and uplift pressure born by the dam.
Under the drive of technologies such as internet of things, internet, cloud computing and the like, dam grouting tends to be gradually automated and intelligentized, massive information data can be accumulated in the period, and the data has the characteristics of complexity, diversity and the like. Therefore, the grouting data acquisition, the filtration, the screening, the smoothing and the visualization of mass grouting data information and the rapid acquisition of valuable information become important technical problems which need to be solved urgently in water engineering construction management.
Disclosure of Invention
The invention aims to provide an intelligent grouting data acquisition, visualization and depth analysis method, which further guarantees the grouting quality and guarantees the intellectualization of the grouting process. The method comprises the following steps:
s01, metadata standard management: the method is used for managing the format, quality, scale, acquisition frequency and transmission frequency of dam grouting survey data, design data, construction data, result data and quality inspection data;
s02, metadata collection management: the method is used for collecting, interacting and storing dam grouting survey data, design data, construction data, result data and quality inspection data;
s03, metadata quality management: the intelligent grouting construction data management system is used for managing the quality of intelligent grouting construction data, achievement data and quality inspection data, and comprises data quality index planning, data quality analysis, data problem statistics and data problem form generation;
s04, data standardization: the method is used for classifying, dividing and standardizing the stored metadata, and realizing the standardization of information such as format, unit, element and the like of the data;
s05, data visualization matching: the method is used for visual matching processing of standardized data, mainly comprises noise reduction, smoothing and feature detection of the data, and completes parametric modeling, three-dimensional space fitting and the like on the basis;
s06, data visualization application: and visualizing the survey data, the design data, the construction data, the result data and the quality inspection data by using the data which is visually matched and processed.
S07, deep data analysis: the method is used for calculating the data basic statistical indexes and analyzing the correlation, and the data deep analysis result is displayed while the data is applied in a visual mode.
Further, in step S01, the survey data includes borehole information, acoustic data before grouting, and full-hole imaging before grouting; the design data comprises grouting hole site arrangement, hole section design, construction hole sequence and construction parameters; the construction data comprises drilling data, pressurized water data, grouting process data, lifting data and construction progress data; the achievement data comprises water permeability and unit ash injection amount; the quality inspection data comprises acoustic data after grouting and full-hole imaging after grouting.
Further, in step S02, the data acquisition is completed based on the sensing device, the image acquisition device and the geophysical prospecting device, and includes a grouting pressure sensor, a grouting flow sensor, a slurry density sensor, a lift monitoring sensor, a temperature monitoring sensor, a time monitoring sensor, an in-hole imaging device, a sound wave emitting and receiving device, and the like.
The data interaction mode includes but is not limited to 4G/5G network, optical fiber, WIFI and Bluetooth.
Further, in the step S03, when the data quality analysis result shows that there is no data quality problem, the step S04 is performed; and when the data quality analysis result indicates that the data quality problem exists, counting the data problem and generating a data problem form, transmitting the form to a grouting construction link, and performing primary screening on the grouting operation quality and troubleshooting of a data acquisition system by taking the data problem form as a basis.
Further, in step S06, the visualization application objects include visualization of grouting construction process, visualization of water permeability change and achievement spatial distribution, visualization of unit ash injection amount change and achievement spatial distribution, visualization of sound wave velocity distribution before and after grouting and improvement condition distribution, and visualization of in-hole imaging spatial distribution.
Further, in step S07, the data basis statistical indicator includes an average value, a dichotomy number, a quartile number, a maximum value, a minimum value, a standard deviation, and a specificity coefficient, and the correlation analysis includes a correlation analysis of a water permeability and a unit ash injection amount.
The invention has the following beneficial effects:
the dam intelligent grouting and engineering geological big data visual analysis method provides necessary foundation for realizing grouting process intellectualization and grouting operation sunshine, and is reliable support for ensuring grouting quality;
secondly, by utilizing a big data analysis display technology, visual display of sound waves, water permeability and unit ash injection amount is realized, and grouting result superposition engineering geological models are displayed in sequence, subsection and interval;
and thirdly, superposing the engineering structure data, the engineering geological data, the grouting result data and the quality inspection data, providing a platform foundation for deeply analyzing the correlation among dam foundation settlement, seepage and grouting result data factors, and providing comprehensive data support for the safety monitoring and evaluation of dam water storage and operation period.
Drawings
FIG. 1 is a general flow chart of a dam intelligent grouting and engineering geological big data visualization analysis method;
FIG. 2 is a schematic diagram of the acquisition and interaction at step S02 in FIG. 1;
fig. 3 is a system configuration diagram of data quality management in step S03 of fig. 1;
fig. 4 is a schematic flowchart of the data visualization application in step S06 in fig. 1.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer and clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the method for visually analyzing the intelligent grouting and engineering geological big data of the dam according to the preferred embodiment of the present invention, as shown in fig. 1, the method for visually analyzing the intelligent grouting and engineering geological big data of the dam comprises the following steps:
step S01, metadata standard management: and (3) determining the format, quality standard, scale, acquisition frequency and transmission frequency of dam grouting survey data, design data, construction data, result data and quality inspection data.
Step S02, metadata collection management: the intelligent grouting and engineering geological data of the dam are divided into survey data, design data, construction data, result data and quality inspection data to be collected and managed. The survey data and the design data can be directly integrated and led into the system, and the system automatically decodes and interprets according to a required format. Wherein the survey data comprises drilling information, acoustic waves before grouting, and full-hole imaging before grouting; the design data includes grouting hole site arrangement, hole segment design, construction hole order and construction parameters. The construction data, the achievement data and the quality inspection data are directly transmitted to the system through various sensors laid on grouting equipment through a 4G/5G internet of things, optical fibers or WIFI. The construction data comprises drilling data, pressurized water data, grouting process data, lifting data and construction progress data; the achievement data comprises water permeability and unit ash injection amount; the quality inspection data comprises acoustic data after grouting and full-hole imaging data after grouting.
Step S03, metadata quality management: construction data, achievement data and quality inspection data acquisition are completed in the intelligent dam grouting construction process and the construction finishing stage, and data quality analysis is carried out. When the data quality analysis result shows that no data quality problem exists, further carrying out an S04 data standardization step; and when the data quality analysis result indicates that the data quality problem exists, counting the data problem and generating a data problem form, transmitting the form to grouting construction and quality inspection links, and performing grouting operation quality primary screening and data acquisition system investigation according to the data problem form.
Step S04, data normalization: in order to realize the standardization of information such as formats, units, quantity and the like of the stored metadata, the metadata standardization is finished by using methods such as classification, segmentation, normalization, dimensionless and the like.
Step S05, data visualization matching processing: visual matching processing of standardized data mainly comprises noise reduction, smoothing and feature detection of the data, and parametric modeling, three-dimensional space fitting and the like are completed on the basis;
step S06, data visualization application: the visual application of the design data and the survey data comprises the visualization of a dam body structure model and an engineering geological model and the visualization of grouting hole arrangement based on the visualization; the visualization application of the construction data and the achievement data is based on the visualization of the design data and the survey data, and comprises the visualization of the grouting construction process, the visualization of the water permeability change and the achievement spatial distribution, and the visualization of the unit ash injection amount change and the achievement spatial distribution; the quality inspection data can be visually overlapped with survey data, and the method comprises the steps of distributing the sound wave speed before and after grouting, improving the condition distribution visualization and the in-hole imaging space distribution visualization.
Step S07, data depth analysis: and calculating and analyzing the correlation of various data basic statistical indexes, including average value, binary number, quartile, maximum value, minimum value, standard deviation, specific coefficient, water permeability and unit ash injection amount. The depth analysis calculation result is displayed while the data is visualized, mouse clicking and box selection are supported on a data visualization interface, and the system automatically completes the depth analysis calculation and display of the selected position data.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise embodiments disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (7)
1. A dam intelligent grouting and engineering geological big data visualization analysis method is characterized by comprising the following steps:
step 1: and (3) carrying out metadata standard management: the method is used for managing the format, quality, scale, acquisition frequency and transmission frequency of dam grouting survey data, design data, construction data, result data and quality inspection data;
step 2: and (3) metadata collection management: the method is used for collecting, interacting and storing dam grouting survey data, design data, construction data, result data and quality inspection data;
and step 3: and (3) performing metadata quality management: the intelligent grouting construction data management system is used for managing the quality of intelligent grouting construction data, achievement data and quality inspection data, and comprises data quality index planning, data quality analysis, data problem statistics and data problem form generation;
and 4, step 4: and (3) carrying out data standardization: the method is used for classifying, dividing and standardizing the stored metadata, and realizing the standardization of information such as format, unit, element and the like of the data;
and 5: performing data visualization matching processing for visualization matching processing of standardized data, mainly comprising noise reduction, smoothing and feature detection of the data, and completing parametric modeling, three-dimensional space fitting and the like on the basis;
step 6: performing data visualization application, and visualizing survey data, design data, construction data, result data and quality inspection data by using the data subjected to visualization matching processing;
and 7: and carrying out data depth analysis for calculation of data basic statistical indexes and correlation analysis, and displaying the data depth analysis result while carrying out data visualization application.
2. The method for visually analyzing the intelligent grouting and engineering geological big data of the dam according to claim 1, wherein in the step 1, the survey data comprises drilling information, acoustic data before grouting, and full-hole imaging before grouting; the design data comprises grouting hole site arrangement, hole section design, construction hole sequence and construction parameters; the construction data comprises drilling data, pressurized water data, grouting process data, lifting data and construction progress data; the achievement data comprises water permeability and unit ash injection amount; the quality inspection data comprises acoustic data after grouting and full-hole imaging after grouting.
3. The method for visually analyzing the intelligent grouting and engineering geological big data of the dam according to claim 1, wherein in the step 2, data acquisition is completed based on a sensing device, an image acquisition device and a geophysical prospecting device.
4. The method for visually analyzing the intelligent grouting and engineering geological big data of the dam according to claim 3, wherein the sensing equipment comprises a grouting pressure sensor, a grouting flow sensor, a slurry density sensor, a lifting monitoring sensor, a temperature monitoring sensor and a time monitoring sensor, the image acquisition equipment comprises in-hole imaging equipment, and the geophysical prospecting equipment comprises sound wave transmitting and receiving equipment.
5. The method for visually analyzing the dam intelligent grouting and engineering geological big data according to one of the claims 1 to 4, characterized in that in step 3, when the data quality analysis result is that no data quality problem exists, step 4 is performed; and when the data quality analysis result indicates that the data quality problem exists, counting the data problem and generating a data problem form, transmitting the form to a grouting construction link, and performing primary screening on the grouting operation quality and troubleshooting of a data acquisition system by taking the data problem form as a basis.
6. The method for visually analyzing dam intelligent grouting and engineering geological big data according to claim 1, wherein in step 6, the visual application objects comprise grouting construction process visualization, water permeability change and achievement space distribution visualization, unit ash injection amount change and achievement space distribution visualization, sound wave velocity distribution before and after grouting, improvement condition distribution visualization and in-hole imaging space distribution visualization.
7. The method for visually analyzing the intelligent grouting and engineering geological big data of the dam according to claim 1, wherein in the step 7, the data basic statistical indexes comprise an average value, a dichotomy number, a quartile number, a maximum value, a minimum value, a standard deviation and a specificity coefficient, and the correlation analysis comprises the correlation analysis of the water permeability and the unit ash injection amount.
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