CN116539009A - New method for cataloging underground exploration engineering based on novel total station scanner - Google Patents
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Abstract
The invention discloses a new method for logging a cave detection project based on a novel total station scanner, which comprises the following steps: step 1, constructing a rear intersection station setting, and setting station leading points by measuring staff through known control points; step 2, acquiring scanned point cloud data through a GTL-1000 total station scanner; step 3, adding points to geological boundary lines; step 4, lofting and sampling; step 5, using magnetCollage to derive point cloud data, using magnetCollage software to check the point cloud data stored by the GTL-1000 total station scanner, checking the three-dimensional form integrity degree of the cave detection engineering by geology personnel, and using a computer algorithm model to dilute the point cloud data; step 6, importing the thinned point cloud data into a professional geological data processing module to realize true three-dimensional simulation of the underground exploration engineering; and 7, perfecting a final drawing piece of the underground exploration project. According to the invention, the GTL-1000 total station scanner is used for carrying out the recording of the underground exploration engineering, so that the recording time and cost of the underground exploration engineering are effectively saved.
Description
Technical Field
The invention relates to the technical field of data information processing, in particular to a new method for tunneling engineering cataloging based on a novel total station scanner.
Background
Currently, most of total stations are used for setting up stations, measuring angles, measuring distances, measuring three-dimensional coordinates, measuring intersection points and lofting, and most of scanners are used for detecting and analyzing shape (geometric configuration) and appearance data (such as color and surface albedo properties) of objects or environments in the real world. The collected data is often used to perform three-dimensional reconstruction calculations, a digital model of the real object in the virtual world. In concrete underground exploration engineering, the conventional field work flow is that a total station is arranged, a rear intersection is carried out, a measurement target is arranged, a scanner is arranged, a scanning target is arranged, scanning is carried out, data processing is carried out, the measurement coordinates of the total station are imported, point clouds are exported through coordinate splicing, and a professional geological data processing module is imported. The conventional scanning flow is very complicated, the carried instruments are more, the required personnel are more, the scanning speed is low, and the data information processing capability is lagged; therefore, how to combine the total station and the scanner into one instrument, improving the working efficiency and saving the production cost is a technical problem to be solved urgently.
Disclosure of Invention
Aiming at the defects of the technology, the invention discloses a new method for compiling a cave detection project based on a novel total station type scanner, wherein in the cave detection project, a GTL-1000 total station type scanner is used for replacing a traditional total station and scanner, and the final drawing is completed by using the steps of station setting, rear intersection, scanning, and leading-in of point cloud data by a Magnet column and leading-in of professional software analysis. The high-speed laser scanning speed of the GTL-1000 total station scanner saves a large amount of field scanning time, the convenient use mode reduces 50% -75% of working procedures, the one-time inspection process is completed in 20 minutes at maximum, meanwhile, the equipment investment and the labor cost are saved, and meanwhile, the data information processing capability is improved.
A new method for logging a cave-in engineering based on a novel total station scanner comprises the following steps:
step 1, constructing a rear intersection station, and realizing station setting introduction by using a rear intersection module in a GTL-1000 total station scanner by a measurer according to a known control point;
step 2, acquiring three-dimensional scanned point cloud data through a GTL-1000 total station scanner, scanning the point cloud data through the GTL-1000 total station scanner by a measurer, measuring geological boundaries, collecting typical geological phenomenon image data, and describing information of each horizon and mineralization alteration data in detail;
step 3, adding points to geological boundary lines;
in the step 3, a measurer realizes each geological boundary line and a structure adding point according to the measurement data in the GTL-1000 total station scanner;
step 4, lofting and sampling;
in the fourth step, a measurer adopts a GTL-1000 total station scanner to loft, and simultaneously adopts special equipment to finish sampling;
step 5, using Magnet Collage to derive point cloud data, using Magnet Collage software to check the point cloud data stored in the SD card of the GTL-1000 total station scanner, using 3D images in the Magnet Collage software to check the integrity degree and boundary point position of the three-dimensional form of the cave detection project by geologists, and using a computer algorithm model to dilute the point cloud data;
step 6, importing the thinned point cloud data into a professional geological data processing module, importing GIS, CAD, micromine software into the thinned point cloud data by geological personnel to realize true three-dimensional simulation of the underground exploration engineering, adopting boundary points to outline geological boundary on a 3D simulation image, and expressing different lithology horizons through different colors;
and 7, perfecting a final drawing of the tunneling project, and adding the occurrence, layered description characters and typical geological phenomenon elements at corresponding positions on the 3D simulation image by geological personnel to complete the tunneling project transcription work.
As a further embodiment of the present invention, the working method of the rear intersection station includes the following steps: :
step one, knowing the coordinates of three points A, B, C in the control points, connecting the three points to form a triangle, and setting the coordinates P of the station as one point in the triangle;
and step two, the GTL-1000 total station scanner calculates the coordinates P of the station by adopting a rear intersection mode according to the known control point coordinates.
Step three, adjusting the distance between the coordinates of the three points A, B, C through an adjusting module, wherein the adjusting module comprises a laser positioning module with a correcting function for positioning the coordinates of the three points A, B, C; positioning for at least 10 times, and evaluating and training the historical data information by means of an Extreme Learning Machine (ELM) module; the extreme learning machine ELM module comprises an input layer, a hidden layer and an output layer;
step four, connecting P points drawn in different times into a line to form a P curve;
and fifthly, evaluating the amplitude value of the P curve, wherein when the error between the peak value and the valley value of the P curve is between 0 and 1, the P point which is set by a user can be normally used, when the error between the peak value and the valley value of the P curve is between 1 and 4, the P point which is set by the user is between 1 and 2, the P point which is set by the user is normally used after the user checks the factors which influence the P point position accuracy, and the user stops using the P point to perform fault checking.
As a further embodiment of the present invention, A, B, C of the known control points are connected to form a triangle, and the coordinates P of the station are set to be a point within Δabc, P A Represents the calculated intermediate quantity of +.A, P A The output function formula is:
in the formula (1), cotA represents the cotangent value of < A, and cotα represents the cotangent value of < BPC;
a, B, C of the known control points are connected to form a triangle, and the coordinates P of the station are set as a point within delta ABC, P B Represents the calculated intermediate quantity of +.B, P B The output function formula is:
in the formula (2), cotB represents the cotangent value of +.b, and cotβ represents the cotangent value of +.apc;
a, B, C of the known control points are connected to form a triangle, and the coordinates P of the station are set as a point within delta ABC, P C Represents the calculated intermediate quantity of < C >, P C The output function formula is:
in the formula (3), cotC represents the cotangent value of < C, and coty represents the cotangent value of < APB;
the GTL-1000 total station scanner calculates the coordinate P of the station by adopting a rear intersection mode according to the known control point coordinate, and the abscissa x of the coordinate P P The output function formula is:
in formula (4), P A 、P B 、P C The calculated intermediate quantity of the angle A, the calculated intermediate quantity of the angle B, the calculated intermediate quantity of the angle C and x are respectively as follows A 、x B 、x C The abscissa of A, B, C, respectively;
the GTL-1000 total station scanner calculates the coordinate P of the station by adopting a rear intersection mode according to the known control point coordinate, and the ordinate y of the coordinate P P The output function formula is:
in formula (5), P A 、P B 、P C The calculated intermediate quantity of the angle A, the calculated intermediate quantity of the angle B, the calculated intermediate quantity of the angle C and y are respectively as follows A 、y B 、y C Respectively A, B, C.
As a further embodiment of the present invention, the GTL-1000 total station scanner obtains three-dimensional scanned point cloud data through a laser scanning module, and the laser measuring module measures geological boundaries, specifically including the following steps:
(1) Starting a GTL-1000 total station scanner, and setting working parameters of an automatic tracking module and an automatic aiming module;
(2) Starting an automatic tracking module, wherein the automatic tracking module comprises a CS5464 chip and an Arduino microcontroller connected with the CS5464 chip, the CS5464 chip is connected with a deviation analysis module and a current conversion module, and the Arduino microcontroller is connected with a clock chip, a communication module, a position tracing chip, a positioning module and an alternating current-direct current converter;
(3) Starting an automatic calibration module, wherein the automatic calibration module comprises a SIM7600CE chip circuit, a communication circuit and a correction circuit, wherein the communication circuit and the correction circuit are connected with the SIM7600CE chip circuit; (4) The GTL-1000 total station scanner realizes point cloud data acquisition through a laser scanning module and presents clear 3D images. .
As a further embodiment of the invention, the GTL-1000 total station scanner realizes automatic rotation through an automatic tracking module and an automatic aiming module;
the automatic tracking module adopts a motor automatic rotating device and a laser transmitting and receiving device to realize automatic tracking, and adopts a rotating speed of 180 degrees/second and a tracking speed of 20 degrees/second to realize high-speed rotation, the prism selection mode of the automatic tracking module comprises 360-degree prism ATP1/ATP1S, a small-sized rod prism R1 PA/prism S and a standard cone prism AP01 AR/prism 2, different modes are selected according to different working scenes to acquire point cloud data, and the automatic sighting module adopts a reflecting plate to realize a sighting function.
As a further embodiment of the invention, the GTL-1000 total station scanner realizes point cloud data acquisition through a laser scanning module; the laser scanning module adopts a scanning frequency of 100000 points/second to realize high-speed scanning, adopts a scanning precision of (+ -2 mm@50m) and a resolution of 500 ten thousand pixels to realize high-precision scanning, and displays a clear 3D image.
As a further embodiment of the invention, the point cloud data is derived by adopting the magnetCollage, the point cloud data stored in the GTL-1000 total station scanner is checked by adopting magnetCollage software, the storage module scanned by the GTL-1000 total station scanner comprises a flash memory storage module and an SD card storage module, the data volume is small, the flash memory storage module is used for storing information, and the SD card module is used for storing information.
As a further embodiment of the invention, the geological personnel can inspect the integrity degree and boundary point positions of the three-dimensional form of the project through the 3D image in the magnetCollage software, and the specific process of the magnetCollage software on the 3D image operation is to fuse the point cloud data of mobile measurement and static scanning, seamlessly integrate the 3D image and mass data, visually analyze the point cloud and reference geography.
As a further embodiment of the present invention, a method for constructing an ELM module of an extreme learning machine includes:
(step 1) setting information of hidden layer nodes, and assuming that the hidden layer nodes are i and the weight is w, outputting a weight vector by the ith hidden layer node as beta and biasing the jth hidden layer node as b j Then connect the relationship between different layers by the inner product, the inner product is recorded as w j。。 x j The method comprises the steps of carrying out a first treatment on the surface of the (step 2) inputting an evaluation sample classification label, and supposing the classification label as m and the evaluation function as m:
(6)
in the formula (6), K represents a data information input function, β j Data information representing the j-th hidden layer calculation output, h () represents the activation function, x j Representing data information of the j-th hidden layer calculation input, h (w j ..+b i ) Representing an extreme learning machine activation function, then the hidden layer output matrix function is represented as:
in the formula (7), M represents an implicit layer output matrix function, and L represents the number of times of calculation;
(step 3), fault judgment and calculation, assuming M to be expressed as a plurality of hidden layer output momentsMatrix functions, dividing M data information into different data sets, and supposing to be marked as multi-source data set s 1 Sum s 2 Then the multisource dataset s 1 Sum s 2 Correlation factor b (l) 1 ， l 2) Is expressed as a function of:
in formula (8), M s And M m Data information representing different source data sets,
and (3) calculating by using a formula (8) to obtain the association factors among different measured values, and further outputting the association degree among the multi-source data sets.
(step 4), outputting a calculation function. Positive beneficial effects
In the underground exploration project catalog, a GTL-1000 total station scanner is used for replacing the traditional total station and scanner, and the final drawing is completed by the steps of station setting, rear intersection, scanning, and leading-in of point cloud data by Magnet college and leading-in of professional software analysis. The high-speed laser scanning speed of the GTL-1000 total station scanner saves a large amount of field scanning time, the convenient use mode reduces 50% -75% of working procedures, the inspection process is completed in 20 minutes at maximum, and meanwhile, the equipment investment and the labor cost are saved. In specific application, the invention can also adjust the distance between the coordinates of the three points A, B, C through the adjusting module, improve the positioning capability, and evaluate and train the historical data information through the mode of the extreme learning machine ELM module; the evaluation capability of the position data information is improved, and the application capability and the calculation capability of the data information are improved by the method.
Drawings
For a clearer description of embodiments of the invention or of solutions in the prior art, the drawings that are necessary for the description of the embodiments or of the prior art will be briefly described, it being apparent that the drawings in the description below are only some embodiments of the invention, from which, without inventive faculty, other drawings can be obtained for a person skilled in the art, in which:
FIG. 1 is a schematic diagram of the overall architecture of a new method for logging a cave-in project based on a novel total station scanner;
FIG. 2 is a schematic view of a rear intersection in a new method of logging a chamber exploration project based on a novel total station scanner;
FIG. 3 is a schematic diagram of the hardware structure of the novel total station scanner in the new method for logging the underground exploration project based on the novel total station scanner;
FIG. 4 is a schematic diagram of the ELM module of the extreme learning machine in the new method of the tunneling project inventory based on the novel total station scanner;
FIG. 5 is a schematic diagram of a SIM7600CE circuit in a new method of entry engineering catalog based on a novel total station scanner;
FIG. 6 is a schematic diagram of an automatic tracking module in a new method of tunneling project inventory based on a novel total station scanner according to the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
As shown in fig. 1-6, a new method for logging a cave detection project based on a novel total station scanner comprises the following steps:
step 1, constructing a rear intersection station, and realizing station setting introduction by using a rear intersection module in a GTL-1000 total station scanner by a measurer according to a known control point;
step 2, acquiring three-dimensional scanned point cloud data through a GTL-1000 total station scanner, scanning the point cloud data through the GTL-1000 total station scanner by a measurer, measuring geological boundaries, collecting typical geological phenomenon image data, and describing information of each horizon and mineralization alteration data in detail;
step 3, adding points to geological boundary lines;
in the step 3, a measurer realizes each geological boundary line and a structure adding point according to the measurement data in the GTL-1000 total station scanner;
step 4, lofting and sampling;
in the fourth step, a measurer adopts a GTL-1000 total station scanner to loft, and simultaneously adopts special equipment to finish sampling;
step 5, using Magnet Collage to derive point cloud data, using Magnet Collage software to check the point cloud data stored in the SD card of the GTL-1000 total station scanner, using 3D images in the Magnet Collage software to check the integrity degree and boundary point position of the three-dimensional form of the cave detection project by geologists, and using a computer algorithm model to dilute the point cloud data;
step 6, importing the thinned point cloud data into a professional geological data processing module, importing GIS, CAD, micromine software into the thinned point cloud data by geological personnel to realize true three-dimensional simulation of the underground exploration engineering, adopting boundary points to outline geological boundary on a 3D simulation image, and expressing different lithology horizons through different colors;
and 7, perfecting a final drawing of the tunneling project, and adding the occurrence, layered description characters and typical geological phenomenon elements at corresponding positions on the 3D simulation image by geological personnel to complete the tunneling project transcription work.
In the invention, when in field work of the underground exploration project record, a GTL-1000 total station scanner can be used for replacing the traditional total station and scanner, and the specific equipment use process comprises station setting, rear intersection, high-speed scanning, geological boundary line measurement, lofting, magnetic column export point cloud data, and leading in professional software GIS, CAD, micromine to analyze the data and complete the record of the final underground exploration project. The high-speed laser scanning of the GTL-1000 total station scanner saves a great deal of field scanning time, reduces the working flow by 50% -75%, finishes the inspection flow for 20 minutes at the highest speed, can finish tasks by a single person in actual operation, and saves equipment investment and labor cost.
In the invention, the working method of the rear intersection station comprises the following steps: :
step one, knowing the coordinates of three points A, B, C in the control points, connecting the three points to form a triangle, and setting the coordinates P of the station as one point in the triangle; specifically, the triangle characteristic is calculated to improve the data information calculation capability;
and step two, the GTL-1000 total station scanner calculates the coordinates P of the station by adopting a rear intersection mode according to the known control point coordinates. Specifically, a curve coordinate of the coordinate P is configured to improve the data information interaction capability;
step three, adjusting the distance between the coordinates of the three points A, B, C through an adjusting module, wherein the adjusting module comprises a laser positioning module with a correcting function for positioning the coordinates of the three points A, B, C; positioning for at least 10 times, and evaluating and training the historical data information by means of an Extreme Learning Machine (ELM) module; the extreme learning machine ELM module comprises an input layer, a hidden layer and an output layer; when correcting data information, position error calculation can be performed in an error information calculation mode, error data information evaluation and calculation are performed through an extreme learning machine ELM module, and data information calculation and evaluation capacity is improved;
step four, connecting P points drawn in different times into a line to form a P curve;
and fifthly, evaluating the amplitude value of the P curve, wherein when the error between the peak value and the valley value of the P curve is between 0 and 1, the P point which is set by a user can be normally used, when the error between the peak value and the valley value of the P curve is between 1 and 4, the P point which is set by the user is between 1 and 2, the P point which is set by the user is normally used after the user checks the factors which influence the P point position accuracy, and the user stops using the P point to perform fault checking.
In the specific application, the field environment can be considered in advance before the underground exploration engineering is recorded, and the control point is determined according to the shape of the mine tunnel, so that the subsequent GTL-1000 total station scanner can conveniently set up stations in a rear intersection mode.
In the present invention, A, B, C of the known control points are connected to form a triangle, and the coordinates P of the station are set as a point within DeltaABC, P A Represents the calculated intermediate quantity of +.A, P A The output function formula is:
in the formula (1), cotA represents the cotangent value of < A, and cotα represents the cotangent value of < BPC;
a, B, C of the known control points are connected to form a triangle, and the coordinates P of the station are set as a point within delta ABC, P B Represents the calculated intermediate quantity of +.B, P B The output function formula is:
in the formula (2), cotB represents the cotangent value of +.b, and cotβ represents the cotangent value of +.apc;
a, B, C of the known control points are connected to form a triangle, and the coordinates P of the station are set as a point within delta ABC, P C Represents the calculated intermediate quantity of < C >, P C The output function formula is:
in the formula (3), cotC represents the cotangent value of < C, and coty represents the cotangent value of < APB;
the GTL-1000 total station scanner calculates the coordinate P of the station by adopting a rear intersection mode according to the known control point coordinate, and the abscissa x of the coordinate P P The output function formula is:
in formula (4), P A 、P B 、P C The calculated intermediate quantity of the angle A, the calculated intermediate quantity of the angle B, the calculated intermediate quantity of the angle C and x are respectively as follows A 、x B 、x C The abscissa of A, B, C, respectively;
the GTL-1000 total station scanner calculates the coordinate P of the station by adopting a rear intersection mode according to the known control point coordinate, and the ordinate y of the coordinate P P Output ofThe function formula is:
in formula (5), P A 、P B 、P C The calculated intermediate quantity of the angle A, the calculated intermediate quantity of the angle B, the calculated intermediate quantity of the angle C and y are respectively as follows A 、y B 、y C Respectively A, B, C.
In specific application, three points capable of forming delta ABC are selected from known control points, a GTL-1000 total station scanner is placed in a triangle, and the degrees of alpha, namely, BPC, beta, namely, APC and gamma, namely, APB are measured through the GTL-1000 total station scanner and used for the GTL-1000 total station scanner to calculate the current position coordinate P of the GTL-1000 total station scanner according to a rear intersection mode.
In the invention, the GTL-1000 total station scanner obtains three-dimensional scanned point cloud data through a laser scanning module, and the laser measuring module measures geological boundaries, and specifically comprises the following steps:
(1) Starting a GTL-1000 total station scanner, and setting working parameters of an automatic tracking module and an automatic aiming module;
(2) Starting an automatic tracking module, wherein the automatic tracking module comprises a CS5464 chip and an Arduino microcontroller connected with the CS5464 chip, the CS5464 chip is connected with a deviation analysis module and a current conversion module, and the Arduino microcontroller is connected with a clock chip, a communication module, a position tracing chip, a positioning module and an alternating current-direct current converter; specifically, under the double control of a CS5464 chip and an Arduino microcontroller, the position tracing is performed to improve the data information computing capability;
(3) Starting an automatic calibration module, wherein the automatic calibration module comprises a SIM7600CE chip circuit, a communication circuit and a correction circuit, wherein the communication circuit and the correction circuit are connected with the SIM7600CE chip circuit; (4) The GTL-1000 total station scanner realizes point cloud data acquisition through a laser scanning module and presents clear 3D images.
In a further embodiment as shown in figure 5,
in the invention, the GTL-1000 total station scanner realizes automatic rotation through an automatic tracking module and an automatic sighting module, wherein the automatic tracking module adopts a motor automatic rotating device and a laser transmitting and receiving device to realize automatic tracking, and adopts a rotating speed of 180 degrees/second and a tracking speed of 20 degrees/second to realize high-speed rotation, the prism selection mode of the automatic tracking module comprises 360-degree prism ATP1/ATP1S, a small-sized rod prism R1 PA/prism S and a standard single prism AP01 AR/prism 2, different modes are selected according to different working scenes to acquire point cloud data, and the automatic sighting module adopts a reflecting sheet to realize a sighting function.
In specific application, the GTL-1000 total station scanner can rapidly acquire point cloud data, and selects a proper prism mode according to different working sites, so that high-precision data acquisition is realized, and clearer 3D images are presented.
In the invention, the GTL-1000 total station scanner realizes point cloud data acquisition through a laser scanning module; the laser scanning module adopts a scanning frequency of 100000 points/second to realize high-speed scanning, adopts a scanning precision of (+ -2 mm@50m) and a resolution of 500 ten thousand pixels to realize high-precision scanning, and displays a clear 3D image.
In particular applications, the high frequency laser scanning of point cloud data by the GTL-1000 total station scanner reduces the amount of measurement time, and the high precision and high pixels of the GTL-1000 total station scanner present clearer 3D images.
In the invention, geological personnel check the integrity degree and boundary point positions of the three-dimensional form of the cave-in engineering through the 3D image in the Magnet Collage software, and the specific process of the Magnet Collage software on the 3D image operation is to fuse the point cloud data of mobile measurement and static scanning, seamlessly integrate the 3D image and mass data, visually analyze the point cloud and reference geography.
In specific application, the Magnet college software integrates point cloud data acquired by scanning by a GTL-1000 total station scanner, namely seamlessly integrating 3D image fragments acquired by each site according to known control point coordinates and coordinates measured by rear intersection, and combining the 3D image fragments into a complete 3D real simulation image of a cave detection project; and drawing different geology with different colors, and delineating different geological boundaries with different measurement data.
As a further embodiment of the present invention, a method for constructing an ELM module of an extreme learning machine includes:
(step 1) setting information of hidden layer nodes, and assuming that the hidden layer nodes are i and the weight is w, outputting a weight vector by the ith hidden layer node as beta and biasing the jth hidden layer node as b j Then connect the relationship between different layers by the inner product, the inner product is recorded as w j 。。x j The method comprises the steps of carrying out a first treatment on the surface of the (step 2) inputting an evaluation sample classification label, and supposing the classification label as m and the evaluation function as m:
(6)
in the formula (6), K represents a data information input function, β j Data information representing the j-th hidden layer calculation output, h () represents the activation function, x j Representing data information of the j-th hidden layer calculation input, h (w j ..+b i ) Representing an extreme learning machine activation function;
in specific application, after different detection data information of the full-combat scanner is converted into data types which can be identified by an ELM module of the extreme learning machine, the identified data information is input into the model in an uninterrupted pair, and the catalogue information is improved through data information coding, so that the method is applied to a big data algorithm model to improve information calculation and application capability.
The hidden layer output matrix function is expressed as:
in the formula (7), M represents an implicit layer output matrix function, and L represents the number of times of calculation;
(step 3), fault judgment and calculation, assuming M to be expressed as a multiple hidden layer output matrix function, dividing M data information into different data sets, and assuming to be recorded as a multi-source data set s 1 Sum s 2 Then the multisource dataset s 1 Sum s 2 Correlation factor b (l) 1 ，l 2 ) Letter of (1)The number is expressed as:
in formula (8), M s And M m Data information representing different source data sets,
and (3) calculating by using a formula (8) to obtain the association factors among different measured values, and further outputting the association degree among the multi-source data sets. In the specific calculation and application process, various input data information can be converted into identifiable information so as to improve the calculation capability of the data information.
(step 4), outputting a calculation function. For user application and implementation.
While specific embodiments of the present invention have been described above, it will be understood by those skilled in the art that these specific embodiments are by way of example only, and that various omissions, substitutions, and changes in the form and details of the methods and systems described above may be made by those skilled in the art without departing from the spirit and scope of the invention. For example, it is within the scope of the present invention to combine the above-described method steps to perform substantially the same function in substantially the same way to achieve substantially the same result. Accordingly, the scope of the invention is limited only by the following claims.
Claims (9)
1. A new method for logging a cave-exploring project based on a novel total station scanner is characterized by comprising the following steps: the method comprises the following steps:
step 1, constructing a rear intersection station, and realizing station setting introduction by using a rear intersection module in a GTL-1000 total station scanner by a measurer according to a known control point; thereby realizing the preparation work of data information acquisition;
step 2, acquiring three-dimensional scanned point cloud data through a GTL-1000 total station scanner, scanning the point cloud data through the GTL-1000 total station scanner by a measurer, measuring geological boundaries, collecting typical geological phenomenon image data, and describing information of each horizon and mineralization alteration data in detail;
step 3, adding points to geological boundary lines;
in the step 3, a measurer realizes each geological boundary line and a structure adding point according to the measurement data in the GTL-1000 total station scanner;
step 4, lofting and sampling;
in the fourth step, a measurer adopts a GTL-1000 total station scanner to loft, and simultaneously adopts special equipment to finish sampling;
step 5, using Magnet Collage to derive point cloud data, using Magnet Collage software to check the point cloud data stored in the SD card of the GTL-1000 total station scanner, using 3D images in the Magnet Collage software to check the integrity degree and boundary point position of the three-dimensional form of the cave detection project by geologists, and using a computer algorithm model to dilute the point cloud data;
step 6, importing the thinned point cloud data into a professional geological data processing module, importing GIS, CAD, micromine software into the thinned point cloud data by geological personnel to realize true three-dimensional simulation of the underground exploration engineering, adopting boundary points to outline geological boundary on a 3D simulation image, and expressing different lithology horizons through different colors;
and 7, perfecting a final drawing of the tunneling project, and adding the occurrence, layered description characters and typical geological phenomenon elements at corresponding positions on the 3D simulation image by geological personnel to complete the tunneling project transcription work.
2. The new method for logging the underground exploration project based on the novel total station scanner as claimed in claim 1, wherein the method comprises the following steps: the working method of the rear intersection station comprises the following steps:
step one, knowing the coordinates of three points A, B, C in the control points, connecting the three points to form a triangle, and setting the coordinates P of the station as one point in the triangle;
step two, the GTL-1000 total station scanner calculates the coordinates P of the station by adopting a rear intersection mode according to the known control point coordinates;
step three, adjusting the distance between the coordinates of the three points A, B, C through an adjusting module, wherein the adjusting module comprises a laser positioning module with a correcting function for positioning the coordinates of the three points A, B, C; positioning for at least 10 times, and evaluating and training the historical data information by means of an Extreme Learning Machine (ELM) module; the extreme learning machine ELM module comprises an input layer, a hidden layer and an output layer;
step four, connecting P points drawn in different times into a line to form a P curve;
and fifthly, evaluating the amplitude value of the P curve, wherein when the error between the peak value and the valley value of the P curve is between 0 and 1, the P point which is set by a user can be normally used, when the error between the peak value and the valley value of the P curve is between 1 and 4, the P point which is set by the user is between 1 and 2, the P point which is set by the user is normally used after the user checks the factors which influence the P point position accuracy, and the user stops using the P point to perform fault checking.
3. The new method for logging the underground exploration project based on the novel total station scanner as claimed in claim 2, wherein the method comprises the following steps: a, B, C of the known control points are connected to form a triangle, and the coordinates P of the station are set as a point within delta ABC, P A Represents the calculated intermediate quantity of +.A, P A The output function formula is:
in the formula (1), cotA represents the cotangent value of < A, and cotα represents the cotangent value of < BPC;
a, B, C of the known control points are connected to form a triangle, and the coordinates P of the station are set as a point within delta ABC, P B Represents the calculated intermediate quantity of +.B, P B The output function formula is:
in the formula (2), cotB represents the cotangent value of +.b, and cotβ represents the cotangent value of +.apc;
a, B, C in the known control points are connected to form a triangle, providedThe coordinates P of the station are points within DeltaABC, P C Represents the calculated intermediate quantity of < C >, P C The output function formula is:
in the formula (3), cotC represents the cotangent value of < C, and coty represents the cotangent value of < APB;
the GTL-1000 total station scanner calculates the coordinate P of the station by adopting a rear intersection mode according to the known control point coordinate, and the abscissa x of the coordinate P P The output function formula is:
in formula (4), P A 、P B 、P C The calculated intermediate quantity of the angle A, the calculated intermediate quantity of the angle B, the calculated intermediate quantity of the angle C and x are respectively as follows A 、x B 、x C The abscissa of A, B, C, respectively;
the GTL-1000 total station scanner calculates the coordinate P of the station by adopting a rear intersection mode according to the known control point coordinate, and the ordinate y of the coordinate P P The output function formula is:
in formula (5), P A 、P B 、P C The calculated intermediate quantity of the angle A, the calculated intermediate quantity of the angle B, the calculated intermediate quantity of the angle C and y are respectively as follows A 、y B 、y C Respectively A, B, C.
4. The new method for logging the underground exploration project based on the novel total station scanner as claimed in claim 1, wherein the method comprises the following steps: the GTL-1000 total station scanner obtains three-dimensional scanned point cloud data through a laser scanning module, and the laser measuring module measures geological boundaries, and the method specifically comprises the following steps of:
(1) Starting a GTL-1000 total station scanner, and setting working parameters of an automatic tracking module and an automatic aiming module;
(2) Starting an automatic tracking module, wherein the automatic tracking module comprises a CS5464 chip and an Arduino microcontroller connected with the CS5464 chip, the CS5464 chip is connected with a deviation analysis module and a current conversion module, and the Arduino microcontroller is connected with a clock chip, a communication module, a position tracing chip, a positioning module and an alternating current-direct current converter;
(3) Starting an automatic calibration module, wherein the automatic calibration module comprises a SIM7600CE chip circuit, a communication circuit and a correction circuit, wherein the communication circuit and the correction circuit are connected with the SIM7600CE chip circuit; (4) The GTL-1000 total station scanner realizes point cloud data acquisition through a laser scanning module and presents clear 3D images.
5. The new method for logging the underground exploration project based on the novel total station scanner as claimed in claim 4, wherein the new method is characterized in that: the GTL-1000 total station scanner realizes automatic rotation through an automatic tracking module and an automatic sighting module, wherein the automatic tracking module adopts a motor automatic rotating device and a laser transmitting and receiving device to realize automatic tracking, and adopts a rotating speed of 180 degrees/second and a tracking speed of 20 degrees/second to realize high-speed rotation, the prism selection mode of the automatic tracking module comprises 360-degree prism ATP1/ATP1S, a small-sized rod prism R1 PA/prism S and a standard single prism AP01 AR/prism 2, different modes are selected according to different working scenes to collect point cloud data, and the automatic sighting module adopts a reflecting sheet to realize a sighting function.
6. The new method for logging the underground exploration project based on the novel total station scanner as claimed in claim 4, wherein the new method is characterized in that: the GTL-1000 total station scanner realizes point cloud data acquisition through a laser scanning module; the laser scanning module adopts 100000 points/second scanning frequency to realize high-speed scanning, adopts + -2 mm@50m scanning precision and 500 ten thousand pixels resolution to realize high-precision scanning, and displays clear 3D images.
7. The new method for logging the underground exploration project based on the novel total station scanner as claimed in claim 1, wherein the method comprises the following steps: and the storage module scanned by the GTL-1000 total station scanner comprises a flash memory storage module and an SD card storage module, the data volume is small, the flash memory storage module is used for storing information, and the data volume is large, and the SD card module is used for storing information.
8. The new method for logging the underground exploration project based on the novel total station scanner as claimed in claim 1, wherein the method comprises the following steps: the geological personnel can inspect the integrity degree and boundary point positions of the three-dimensional form of the engineering through the 3D image in the Magnet Collage software, and the specific process of the Magnet Collage software on the 3D image operation is to fuse the point cloud data of mobile measurement and static scanning, seamlessly integrate the 3D image and mass data, visually analyze the point cloud and reference geography.
9. The new method for logging the underground exploration project based on the novel total station scanner as claimed in claim 1, wherein the method comprises the following steps: the construction method of the ELM module of the extreme learning machine comprises the following steps:
(step 1) setting information of hidden layer nodes, and assuming that the hidden layer nodes are i and the weight is w, outputting a weight vector by the ith hidden layer node as beta and biasing the jth hidden layer node as b j Then connect the relationship between different layers by the inner product, the inner product is recorded as w j 。。x j The method comprises the steps of carrying out a first treatment on the surface of the (step 2) inputting an evaluation sample classification label, and supposing the classification label as m and the evaluation function as m:
in the formula (6), K represents a data information input function, β j Representing j-th hidden layer calculation outputAnd h (-) represents the activation function, x j Representing data information of the j-th hidden layer calculation input, h (w j ..+b i ) Representing an extreme learning machine activation function, then the hidden layer output matrix function is represented as:
in the formula (7), M represents an implicit layer output matrix function, and L represents the number of times of calculation;
(step 3), fault judgment and calculation, assuming M to be expressed as a multiple hidden layer output matrix function, dividing M data information into different data sets, and assuming to be recorded as a multi-source data set s 1 Sum s 2 Then the multisource dataset s 1 Sum s 2 Correlation factor b (l) 1 ，l 2 ) Is expressed as a function of:
in formula (8), M s And M m Data information representing different source data sets,
calculating by using a formula (8) to obtain association factors among different measured values, and further outputting association degrees among multiple source data sets;
(step 4), outputting a calculation function.
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