A Method and System for Collaborative Acquisition of Engineering Survey Data Based on Pre-deployment Guidance

Abstract

This invention relates to the field of engineering data acquisition technology, and in particular to a collaborative acquisition method and system for engineering survey data based on pre-deployment guidance; it includes the following steps: S1, setting up a pre-filled field database; S2, setting up a semi-structured template, setting pre-filled fields and fields to be filled; S3, locating the location points to be collected for field personnel through dual-mode positioning, automatically loading the pre-filled values ​​of the location points to be collected, and simultaneously acquiring core photos, fracture features, and corrected coordinates of each borehole; S4, synchronously recording the acquired core photos, fracture features, corrected coordinates of the boreholes, and corrected permeability levels into the fields to be filled in the semi-structured template in real time; S5, loading a three-dimensional scene onto the boreholes after the completion of field surveys; improving the synergy between office and field work, and increasing the efficiency of engineering survey data acquisition.

Description

Technical Field

[0001] This invention relates to the field of engineering data acquisition technology, and in particular to a collaborative acquisition method and system for engineering survey data based on pre-deployment guidance. Background Technology

[0002] Construction engineering survey refers to the activities of surveying, exploring, and testing topographical, geological, and hydrological conditions to meet the needs of planning, design, construction, operation, and comprehensive management of engineering projects, and providing corresponding results and data. For the planning, design, construction, operation, and comprehensive management of urban construction, industrial and civil buildings, railways, roads, etc., engineering survey provides basic data for feasibility evaluation and construction through surveying, exploring, testing, and comprehensively evaluating topographical, geological, and hydrological elements. It is a primary link in basic construction, and is of great significance in conducting detailed feasibility studies of construction sites, ensuring the rational implementation of projects, and promoting the achievement of optimal economic, social, and environmental benefits.

[0003] Currently, traditional engineering surveys mainly rely on field personnel to record data on-site. Office personnel need to re-enter the recorded data, which results in problems such as low efficiency, easy errors and omissions, and poor coordination. At the same time, field personnel lack pre-set data guidance and need to repeatedly enter basic information. The preliminary research results of office personnel cannot directly guide field operations.

[0004] Therefore, there is an urgent need to provide a collaborative acquisition method and system for engineering survey data based on pre-deployment guidance, which can improve the synergy between indoor and outdoor work and increase the efficiency of engineering survey data acquisition compared with existing technologies. Summary of the Invention

[0005] This invention addresses the technical problems existing in the prior art and provides a method and system for collaborative acquisition of engineering survey data based on pre-deployment guidance.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] The collaborative acquisition method for engineering survey data based on pre-deployment guidance includes the following steps:

[0008] S1. Set up a pre-filled field database to store the exploration data in the office;

[0009] S2. Set up a semi-structured template. In the semi-structured template, set pre-filled fields and fields to be filled. Pre-filled fields are confirmed by pre-filled values ​​in the pre-filled field database, and fields to be filled are confirmed based on fieldwork.

[0010] S3. Through dual-mode positioning, locate the positioning points to be collected by field personnel, automatically load the pre-filled values ​​of the positioning points to be collected, and simultaneously acquire the core photos of each borehole, the fracture characteristics of the borehole, and the corrected coordinates of the borehole.

[0011] S4. The core photos, voice fracture features, corrected coordinates of the loaded borehole, and corrected permeability level obtained in step S3 are all synchronously entered into the fields to be filled in the semi-structured template in real time.

[0012] S5. Load the 3D scene onto the boreholes after the field survey is completed.

[0013] Furthermore, in step S1, the office exploration data includes the exploration line number, the number of each borehole, the design coordinates of each borehole, and the permeability grade of the soil and rock in the exploration area.

[0014] Furthermore, in step S2, all data in the pre-filled fields and fields to be filled in the semi-structured template pass the uniqueness check, and each data item is uniquely assigned a number.

[0015] Furthermore, the uniqueness verification method in step S2 is as follows:

[0016] S21. Create a hash index in the pre-filled field database, using the exploration line number as the key value;

[0017] S22. When an office worker enters a new number, the system executes the following: a. Calculate the hash value of the entered number; b. Check if there is a duplicate hash value in the hash table; c. If there is, perform a full field comparison to confirm whether it is a duplicate; d. If it is confirmed to be a duplicate, prevent saving and prompt "Number already exists".

[0018] S23. Use a Bloom filter for rapid prediction;

[0019] S24. Response time should be controlled within 0.3s.

[0020] Furthermore, the dual-mode positioning method in step S3 is as follows: a hardware layer is set up, integrating the ATGM336H chipset, which supports BeiDou B1I / B2I and GPS L1 / L5 frequency bands; in the hardware layer, the Kalman filter algorithm is used to fuse the original positioning data with multi-satellite system data, and then the local base station signal is accessed via RTK for differential correction. In areas where the signal is blocked, the MEMS inertial navigation unit is enabled to continue positioning, thereby obtaining the positioning data to be collected by the field personnel.

[0021] Furthermore, in step S3, the R-tree spatial indexing method is used to automatically load the pre-filled values ​​of the location points to be collected.

[0022] Furthermore, in step S3, the corrected coordinates of the borehole are obtained by correcting the design coordinates of the borehole. The specific method is as follows: the actual position of the borehole is measured on-site using an RTK probe, the measured coordinates are displayed on the APP, and the deviation vector between the design coordinates and the measured coordinates is displayed. The system then updates the measured coordinates to the corrected coordinates.

[0023] Furthermore, the corrected permeability grade obtained in step S4 is confirmed based on the K value. The permeability grades include very low permeability, low permeability, weak permeability, moderate permeability, strong permeability, and very high permeability.

[0024] Furthermore, the relationship between permeability grade and K value is as follows:

[0025] when At one time, it is extremely permeable; when At that time, it is slightly permeable; when At that time, it is slightly permeable; when At that time, it is moderately permeable; when At that time, it is highly permeable; when At that time, it was extremely permeable.

[0026] The pre-deployed guided collaborative acquisition system for engineering survey data includes a first module, a second module, a third module, a fourth module, and a fifth module. The first module is used to execute step S1, the second module is used to execute step S2, the third module is used to execute step S3, the fourth module is used to execute step S4, and the fifth module is used to execute step S5.

[0027] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0028] (1) This invention effectively improves field data collection time and reduces data collection time by 30%: pre-filled fields avoid repeated input, and voice input replaces manual input; the error rate is reduced by 50%: numbering is automatically verified, and preset dictionary values ​​(such as the permeability level formula) constrain the input range.

[0029] (2) This invention enables collaborative optimization of pre-research results (such as geological analysis), and directly guides field work through pre-deployment, thus achieving a closed loop of knowledge transfer. The three-dimensional scene pre-set tasks are linked with the APP in real time, supporting field personnel to "follow the map to find the task".

[0030] (3) Business value of the present invention: shortens project cycle: pre-deployment and dynamic guidance accelerate field work progress (refer to the statistical requirements of "field active personnel trend"). Reduces labor costs: reduces the workload of data cleaning in the office and focuses on core analysis (such as "survey point collection trend" analysis). Attached Figure Description

[0031] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0032] The technical solution of the present invention will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are not all embodiments of the present invention. All other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention. It should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," etc., indicating the orientation or positional relationship are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description. They do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0033] like Figure 1 As shown, this invention provides a collaborative data acquisition method for engineering surveys based on pre-deployment guidance, comprising the following steps:

[0034] S1. Set up a pre-filled field database to store the exploration data in the office. The exploration data in the office includes exploration lines and boreholes, specifically including the exploration line number, the number of each borehole, the design coordinates of each borehole, and the permeability level of the soil and rock in the exploration area.

[0035] S2. Set up a semi-structured template. In the semi-structured template, set pre-filled fields and fields to be filled. The pre-filled fields are determined by the pre-filled values ​​obtained from the pre-filled field database. The fields to be filled include actual core photos, fracture characteristics, and corrected coordinates. The fields to be filled are entered by field personnel.

[0036] All values ​​in the semi-structured template undergo mandatory uniqueness verification, and duplicate numbers are intercepted in real time with a response time of less than 0.3 seconds, ensuring the uniqueness of each value number and avoiding number conflicts.

[0037] The specific method for uniqueness verification is as follows:

[0038] S21. Create a hash index in the pre-filled field database, using the exploration line number as the key value.

[0039] S22. When an office worker enters a new number, the system performs the following: a. Calculates the hash value of the entered number; b. Queries whether a duplicate hash value exists in the hash table; c. If it exists, performs a full field comparison to confirm whether it is a duplicate; d. If it is confirmed to be a duplicate, it prevents saving and prompts "Number already exists".

[0040] S23. Use a Bloom filter for rapid prediction to reduce database query pressure.

[0041] S24. Response time is controlled within 0.3s, and the query is accelerated by caching recently used numbers in memory.

[0042] S3. Using dual-mode positioning, locate the positioning point to be collected by the field personnel. Using R-tree spatial indexing, automatically load the pre-filled values ​​of all boreholes within a radius of 300m centered on the positioning point to be collected. For the loaded boreholes, the field personnel obtain core photos of each borehole by taking core photos. They also obtain the voice fracture characteristics of each borehole by describing the fracture characteristics of each borehole by voice. Finally, they obtain the corrected coordinates of the loaded boreholes by correcting the design coordinates of the boreholes.

[0043] The specific method of dual-mode positioning is as follows: A hardware layer is set up, integrating the ATGM336H chipset, supporting BeiDou B1I / B2I and GPS L1 / L5 frequency bands. Within this hardware layer, a Kalman filter algorithm is used to fuse the original positioning data with data from multiple satellite systems. Then, differential correction is performed using RTK to connect to the local base station signal. In areas with signal obstruction, a MEMS inertial navigation unit is activated to continue positioning, thereby obtaining the positioning points to be collected by field personnel. The dual-mode positioning method can achieve a horizontal accuracy of less than or equal to 0.5m with a 95% confidence level in open environments; and a horizontal accuracy of less than or equal to 2m in obstructed environments.

[0044] The specific method for R-tree spatial indexing is as follows: 1. Index construction: a. Using the minimum bounding rectangle (MBR) of exploration points as the basic unit; b. Using a variant of R* tree and optimizing the node splitting strategy. 2. Query optimization: a. Establishing a spatial query cache to store recent query results; b. Implementing a batch nearest neighbor query algorithm, supporting millisecond-level return for all exploration points within a 300m radius. 3. Dynamic updates: a. Automatically updating the R-tree structure when adding new exploration points; b. Using a lazy update strategy to balance real-time performance and efficiency.

[0045] The corrected coordinates of the borehole are obtained by correcting the design coordinates of the borehole. The specific method is as follows: field personnel use an RTK probe to measure the actual position of the borehole in the field and obtain high-precision coordinates (accuracy ≤ 2cm); the APP automatically pops up the correction interface, which displays the deviation vector (ΔX, ΔY, ΔZ) between the design coordinates and the measured coordinates; after personnel confirmation, the system updates the measured coordinates to the corrected coordinates and records the reason for the correction (such as "terrain obstacles" or "design offset").

[0046] Using an embedded formula engine, the K-value is calculated in real time based on the corrected coordinates of the borehole, and the permeability grade is automatically converted based on the K-value. The permeability grades include extremely low permeability, very low permeability, weak permeability, moderate permeability, high permeability, and extremely high permeability. The relationship between these grades and the K-value is shown in Table 1.

[0047] Table 1

[0048]

[0049] S4. The core photos, voice fracture features, corrected coordinates of the loaded borehole, and corrected permeability level obtained in step S3 are all synchronously entered into the fields to be filled in the semi-structured template in real time. The pre-filled values ​​corrected after the field exploration in step S3 are locked, and a borehole columnar section is generated. The borehole is marked with the words "verified" on the borehole columnar section.

[0050] S5. Load the 3D scene of the borehole after the completion of the field survey, render the GIS base map using WebGL, and the loading rate is greater than or equal to 50 FPS.

[0051] The collaborative acquisition system for engineering survey data based on pre-deployment guidance provided by the present invention includes a first module, a second module, a third module, a fourth module and a fifth module. The first module is used to execute step S1, the second module is used to execute step S2, the third module is used to execute step S3, the fourth module is used to execute step S4 and the fifth module is used to execute step S5.

[0052] This invention effectively improves field data collection time, reducing collection time by 30%: pre-filled fields avoid repeated input, and voice input replaces manual input; the error rate is reduced by 50%: automatic number verification and preset dictionary values ​​(such as penetration level formulas) constrain the input range.

[0053] This invention enables collaborative optimization of preliminary research results (such as geological analysis), directly guiding fieldwork through pre-deployment and achieving a closed-loop knowledge transfer mechanism. Pre-set tasks in the 3D scene are linked in real-time with the app, allowing field personnel to easily navigate to tasks based on the provided map.

[0054] The business value of this invention lies in shortening project cycles: pre-deployment and dynamic guidance accelerate fieldwork progress (refer to the statistical requirements for "fieldwork activity trends"). It also reduces labor costs: decreasing the workload of data cleaning in office work and allowing for a focus on core analysis (such as "survey point collection trend analysis").

[0055] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, and is not intended to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions made by those skilled in the art to the technical solution of the present invention do not depart from the essence and scope of the technical solution of the present invention.

Claims

1. A method for collaborative acquisition of engineering survey data based on pre-deployment guidance, characterized in that, Comprise the following steps: S1, set up a pre-filled field database for storing internal exploration data; internal exploration data includes the number of exploration lines, the number of each drill hole, the design coordinates of each drill hole, the permeability grade of the rock-soil in the exploration area, etc. S2, set up a semi-structured template, in which pre-filled fields and to-be-filled fields are set up, the pre-filled fields are confirmed by pre-filled values in the pre-filled field database, and the to-be-filled fields are confirmed according to field work; all data in the pre-filled fields and the to-be-filled fields in the semi-structured template are subjected to unique verification, and the number of each data is uniquely set; the unique verification method is: S21, establish a hash index in the pre-filled field database, taking the number of exploration lines as the key value; S22, when an internal staff member inputs a new number, the system performs: a, calculates the hash value of the input number; b, queries whether there is the same hash value in the hash table; c, if there is, it is confirmed whether it is repeated by full field comparison; d, if it is confirmed to be repeated, it is prevented from being saved and prompts "the number already exists"; S23, use a Bloom filter for quick pre-judgment; S24, the response time is controlled within <0.3s; S3, locate the to-be-collected positioning points of the field staff through dual-mode positioning, automatically load the pre-filled values of the to-be-collected positioning points, and simultaneously acquire the core photos of each drill hole, the fracture characteristics of the drill hole, and the corrected coordinates of the drill hole; the dual-mode positioning method is: set up a hardware layer, integrate an ATGM336H chip set, and support Beidou B1I / B2I and GPS L1 / L5 frequency bands; in the hardware layer, use Kalman filtering algorithm to fuse the original positioning data with multi-satellite system data, then access the local reference station signal for differential correction through RTK technology, and enable the MEMS inertial navigation unit to continue positioning in the signal shielding area, so as to obtain the to-be-collected positioning of the field staff; the design coordinates of the drill hole are corrected to obtain the corrected coordinates of the drill hole, and the specific method is: use an RTK probe to measure the actual position of the drill hole, the measured coordinates, the APP end displays the deviation vector of the design coordinates and the measured coordinates, and the system updates the measured coordinates to the corrected coordinates S4, the core photos, the fracture characteristics of the drill hole, the loaded corrected coordinates of the drill hole, and the corrected permeability grade obtained in step S3 are all real-time synchronized into the to-be-filled fields in the semi-structured template; S5, load the three-dimensional scene for the drill hole after the field survey is completed.

2. The pre-deployment guidance-based engineering survey data collaborative acquisition method according to claim 1, characterized in that, In step S3, the R-tree spatial index method is used to automatically load the pre-filled values of the to-be-collected positioning points. 3.The pre-deployment guidance based engineering survey data collaborative acquisition method of claim 1, wherein, The corrected permeability grade obtained in step S4 is confirmed according to the K value, and the permeability grade includes extremely slight water permeability, slight water permeability, weak water permeability, medium water permeability, strong water permeability, and extremely strong water permeability.

4. The pre-deployment guidance-based engineering survey data collaborative acquisition method according to claim 3, characterized in that, The relationship between the permeability grade and the K value is: When , it is very slightly permeable; when , it is slightly permeable; when , it is weakly permeable; when , it is moderately permeable; when , it is strongly permeable; and when , it is very strongly permeable.

5. The engineering survey data collaborative acquisition system based on pre-deployment guidance, characterized in that, The method for collaborative collection of engineering exploration data based on pre-planned guidance according to any one of claims 1-4 is used, comprising a first module, a second module, a third module, a fourth module, and a fifth module, the first module is used to execute step S1, the second module is used to execute step S2, the third module is used to execute step S3, the fourth module is used to execute step S4, and the fifth module is used to execute step S5.

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