Level measurement example generation method and teaching auxiliary system

Abstract

The invention discloses a leveling example generation method and a teaching auxiliary system, and belongs to the technical field of surveying and mapping teaching. The core of the method comprises the following steps: deducing a theoretical observation value through reverse calculation based on a known benchmark elevation and a measurement section distance; dynamically generating an observation record with a random error in combination with an error parameter within a standard tolerance; for an attachment route, a closed loop and a leveling network, a closing error is automatically distributed and a full-mean error / accidental-mean error is calculated. The system module comprises a route design module which supports diversified format data import and dynamically adjusts route levels and structures; the observation simulation module is used for realizing height difference and distance reverse derivation and error simulation; the handbook output module is used for generating a training handbook containing key field spaces according to a standard format; and the intelligent scoring module automatically verifies the submitted result of the user and scores the submitted result. The method solves the problem of lack of examples in teaching and competition, realizes automatic generation and intelligent evaluation of diversified and standardized leveling training examples, provides an efficient tool for surveying and mapping major teaching and skill competition, and has outstanding practical value.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of surveying and mapping teaching, and particularly relates to a leveling measurement auxiliary teaching example generation method and system based on reverse calculation and random error simulation. The system can automatically generate leveling measurement observation records and observation notebooks that meet different levels and different leveling routes, and realize intelligent checking of calculation results, and is suitable for surveying and mapping professional teaching and skill competition training. BACKGROUND

[0002] As a basic supporting discipline of geography, engineering, architecture and other disciplines, surveying practice teaching can cultivate students' practical operation skills, help them understand and master knowledge more deeply, and strengthen their instrument operation ability, data processing ability and problem analysis ability. As a basic measurement work, the internal calculation process of leveling measurement (such as distribution of closing error and height difference adjustment) involves complex theoretical derivation and standard application, which is the focus and difficulty in teaching. Students need to practice a large number of diversified examples to deeply understand the calculation principle and master the operation process.

[0003] The current leveling measurement teaching and skill training faces significant constraints: on the one hand, the leveling examples provided by the teaching materials and commonly used resources are generally single, fixed and idealized, which cannot effectively simulate different precision levels, complex route structures and various random observation errors that inevitably exist in actual work; on the other hand, the high-intensity training for vocational surveying and mapping skill competition requires a large number of high-quality examples that meet the specifications, contain controllable errors and are close to real combat scenes, but the manual preparation method is extremely inefficient and cannot meet the needs. These two problems make it difficult for students and players to obtain sufficient and effective calculation training, which restricts the improvement of teaching effect and competition level.

[0004] The application proposes a leveling measurement example generation method and teaching auxiliary system, which combines reverse calculation and random error simulation to realize the automatic, batch and standardized generation of leveling measurement training examples, and has an intelligent checking function. This not only changes the teaching mode that relies on single textbook cases, provides students with diversified training materials close to real scenes, and significantly improves their internal calculation ability and error analysis ability; but also efficiently supports the high-intensity training needs of skill competition players, quickly generates diversified and massive examples, effectively improves training efficiency and competition level, and has important practical value for promoting surveying and mapping practice teaching reform and competition level improvement. SUMMARY

[0005] The present invention aims to solve the problems of low automation level of example generation, single example and low efficiency of result verification in leveling teaching. The core is to propose a leveling example generation method and system based on inverse calculation and random error simulation. The method takes the known leveling route results (elevation, distance) as the starting point, reversely deduces the theoretical observation values ​​that meet the specifications, and introduces controllable random observation errors (such as sight distance difference, closure difference, Kiev division difference, etc.), and finally automatically generates an observation notebook containing the original observation data, a calculation notebook with reserved key calculation fields and the corresponding standard answers. The system has the function of automatic comparison and scoring of the calculation results submitted by users, providing closed-loop support for teaching and competition training.

[0006] To achieve the above technical objectives and the above technical effects, the present invention is implemented through the following technical solutions: a method and system for generating auxiliary teaching examples for leveling surveying in surveying, the specific contents of which are:

[0007] 1. Method for generating distance and height difference observation records for each measurement round.

[0008] S1 obtains the distance d between each measuring section on the leveling route i and height difference h i , and the length L of the leveling route.

[0009] S2 randomly generates the sight distance difference ΔS of each measuring station within the specification limit i , and calculate the cumulative difference in sight distance before and after any station S i (Unit: m), S i It should meet the tolerance requirements of each level measurement in the specification, see formula (1):

[0010] S i =∑ΔS i (1)

[0011] S3 is based on the distance d of each measuring section i , front and rear sight distance difference ΔS i , calculate the backsight distance D of each measuring station Bi and front sight distance D Fi (Unit: m), D Bi 、D Fi The tolerance requirements of each level measurement in the specification should be met, see formulas (2) and (3):

[0012]

[0013] S4 randomly generates the backsight lower wire reading R at each measuring station BLi , calculate the rear sight wire reading R BUi (Unit: mm) (To simulate the actual observation process, the readings of the upper, middle and lower wires of the level can meet the specification requirements. If the height difference h of a certain measuring station j ′>0, then RBLi The value range is (0.5+h′ i )~(1+h′ i ); if the height difference of the measuring station is h′ j <0, then R BLi The value range is (2-h′ i )~(2.5-h′ i ) between) see formula (4):

[0014] R BUi =R BLi +D Bi ×1000 (4)

[0015] S5 randomly generates the difference α between the average value of the upper and lower wire readings and the middle wire reading within the specification limit Bi Calculate the backsight reading R of each station's basic division PBMi (Unit: mm), see formula (5):

[0016]

[0017] S6 randomly generates the difference β of the height difference measured by the Kiev division within the standard limit i , calculate the basic division height difference h of each measuring station Pi and the height difference of the auxiliary scale h Ai , that is, the value of the wire reading in the rear sight minus the value of the wire reading in the front sight (unit: mm), see formula (6) and (7):

[0018]

[0019] S7 calculates the front sight middle wire reading R of the basic scale at each measuring station PFMi (Unit: mm), see formula (8):

[0020] R PFMi =R PBMi -h Pi (8)

[0021] S8 randomly generates the difference α between the average value of the upper and lower wire readings and the middle wire reading within the specification limit Fi , calculate the front sight wire reading R of each measuring station FUi and the forward sight wire reading R FLi (Unit: mm), see formulas (9) and (10):

[0022]

[0023] S9 randomly generates the difference between the backsight Kiev scale readings γ Bi , calculate the difference γ between the Kiev scale readings of the front sight distance at each measuring station Fi (Unit: mm), γ FiIt should meet the tolerance requirements of each level measurement in the specification, see formula (11):

[0024] γ Fi =γ Bi -β i (11)

[0025] S10 generates the Kiev scale value K and calculates the middle wire reading R of the backsight auxiliary scale at each measuring station ABMi , see formula (12), the front sight auxiliary scale middle wire reading R AFMi The calculation method is the same as R ABMi (Unit: mm).

[0026] R ABMi =R PBMi +K-γ Bi (12)

[0027] 2. The method of generating leveling route calculation examples is provided.

[0028] S1 obtains the elevation H of n leveling points on the leveling route j (j=1,2……n) and the distance d of each measuring section i (i=1,2……n-1), calculate the theoretical height difference h′ of each measuring section i (unit: m; i = 1, 2 ... n-1) and the length of the leveling route L (unit: km), see formulas (13) and (14):

[0029] h i ′=H j+1 -H j (13)

[0030] L=(∑d i ) / 1000 (14)

[0031] S2 randomly generates the specification limit error and line closure error f h , taking the length of each station section as the weight, f h Assign to each measuring station and calculate the "observed" height difference h of each measuring station i (Unit: mm), see formula (15):

[0032]

[0033] S3 randomly generates various correction coefficients within the specification limits and calculates various correction values, including the normal level surface non-parallelism correction ε and the level rod length correction δ. Among them, the first and second class leveling measurements should also calculate the level rod temperature correction а, the gravity anomaly correction λ and the solid tide correction υ, and add the above correction values ​​to the leveling line (the above corrections may not be made in surveying teaching and engineering surveying competition training).

[0034] S4 randomly generates the round trip height difference discrepancy value Δ within the specification limit, and calculates the accidental mean error M per kilometer of leveling measurement Δ , see formula (16), M Δ The specification tolerance requirements should be met.

[0035]

[0036] S5 distributes Δ evenly to the height difference between the forward and return measurement stations, see formulas (17) and (18)

[0037]

[0038] S6: Calculate the observation records of each measuring station for the forward and return measurements of the route according to the method described in Invention Content 1.

[0039] 3. Method for generating closed loop leveling route calculation examples.

[0040] S1 obtains the elevation H of n leveling points on the closed loop leveling route j (j=1,2……n) and the distance d of each measuring section i (i=1,2……n), calculate the theoretical height difference h′ of each measuring section i (unit: m; i = 1, 2...n) and the closed loop length F (unit: km), see formulas (19)-(21):

[0041] h′ i =H j+1 -H j (i=1,2……n-1) (19)

[0042] h′ n =H1-H n (20)

[0043] F=(∑d i ) / 1000 (21)

[0044] S2 randomly generates the inner loop closure error W within the specified tolerance limit, distributes W to each station with the length of the measuring section of each station as the weight, and calculates the "observed" height difference h of each station. i (Unit: mm), see formula (22):

[0045]

[0046] S3 calculates the observation records of each station of the closed-loop leveling route according to the method described in S3-S6 in Invention Content 2.

[0047] 4. Method for generating leveling network calculation examples with more than 20 leveling rings. The specific features are as described in the invention content 3, except that after completing the calculation of the ring closure error W, it is also necessary to calculate the total mean error M per kilometer of leveling measurement. W , see formula (1), M W The specification tolerance requirements should be met.

[0048]

[0049] Where: W is the leveling loop closure error (unit: mm), F is the circumference of the leveling loop (unit: km), and N is the number of leveling loops.

[0050] 5. Construction of teaching auxiliary system.

[0051] S1 Leveling Route Design Module

[0052] S1.1 Leveling route input. Supports importing leveling point results data, including .shp, .dwg, .txt and other formats, and visualizes the read leveling route.

[0053] S1.2 Leveling route adjustment. Dynamically configure the leveling route grade, route form (conformal / closed / node network) and observation instrument type, and perform coordinate translation and elevation adjustment through manual adjustment or automatic generation to generate a variety of leveling route maps that meet the standard tolerances.

[0054] S2 Observation record simulation module: Based on the methods of invention contents 1-5, and in accordance with the relevant technical indicators of the specification, a complete observation data set with random errors is generated through reverse deduction of height difference and distance, observation value simulation and error simulation.

[0055] The S3 notebook custom output module generates an observation dataset simulated in S2 according to the standard format of the leveling notebook. Key fields such as "Sight Distance Difference," "Kiev Differentiation Difference," and "Height Difference" are randomly left blank. The output includes a practice notebook containing the closure error allocation process and a complete derivation of the full mean error calculation steps.

[0056] The S4 intelligent scoring and feedback module analyzes student calculation notebooks according to the level measurement-specific testing rules, compares the correctness of each cell in the notebook, marks cells with calculation errors, and provides instant scoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0058] Figure 1 Generate a flow chart of the method for leveling observation records;

[0059] Figure 2 Generate a teaching aid system module diagram for leveling measurement examples;

[0060] Figure 3 To comply with the leveling route diagram;

[0061] Figure 4 This is a schematic diagram of a closed leveling route;

[0062] Figure 5 Schematic diagram of a leveling network with more than 20 leveling rings;

[0063] Figure 6 Calculate the order and results for the observation notebook;

[0064] Figure 7 Leveling observation record sheet DETAILED DESCRIPTION

[0065] Figure 1 、 Figure 2 This is a flow chart of a method for generating leveling measurement examples and a teaching auxiliary system. This embodiment uses a leveling route as an example to illustrate the method for generating leveling measurement examples and the teaching auxiliary system. The detailed steps are as follows:

[0066] S1 level route graphic design

[0067] S1.1 Route design module reads the known leveling line and obtains the elevation value H of each leveling point j The distance d between each measuring section i The leveling route results table in this embodiment is shown in Table 1.

[0068] Table 1 Leveling route results (m)

[0069]

[0070]

[0071] S1.2 After selecting the leveling route grade, leveling route type and observation instrument, the system automatically adjusts the relevant random number limit errors, such as closure error, sight distance error, etc.

[0072] S1.3 dynamically adjusts the elevation values ​​of leveling points and the distances between leveling route segments through coordinate translation and elevation changes, generating diverse leveling routes.

[0073] S2 Leveling measurement example generation: According to the method described in Invention Summary 1, distance back calculation, height difference back calculation and level reading back calculation are performed in sequence to reversely generate leveling measurement observation records.

[0074] S2.1 Back calculation of leveling distance, by randomly generating the sight distance difference ΔS of each measuring section within the specification limit i , in this embodiment, ΔS i The value range is -1m to 1m, and the front and rear sight distance observation values ​​D of each measurement section are generated in reverse Bi 、D Fi Cumulative difference S i , where D Bi 、D Fi Should not be greater than 50m, S i The absolute value of should not be greater than 3m. The distance backcalculation results in this embodiment are shown in Table 2.

[0075] Table 2 Distance backcalculation results (m)

[0076]

[0077] S2.2 Back calculation of leveling height difference, randomly generate closure error f within the specification limit h , Standard requirements for second-class leveling In this embodiment, h =2.81mm, f h The height difference theoretical value of each measuring section is allocated according to the weight of each measuring section distance to generate the height difference with observation error. The height difference backcalculation result in this embodiment is shown in Table 3.

[0078] Table 3 Height difference back calculation results

[0079]

[0080] S2.3 Level reading back calculation,

[0081] According to the calculation order of the observation notebook, the values ​​of each reading in the notebook are simulated and calculated in sequence. In this embodiment, the Kiev scale value K = 3015.5, and the difference α between the average value of the upper and lower wire readings and the middle wire reading is randomly generated. Bi The absolute value of should be less than 3mm, and the difference of height difference measured by Kiev scale β i The value range is -0.6mm~0.6mm, the difference between the front and rear sight distance Kiev scale readings γ Fi , γ Bi The absolute value of should not be greater than 0.4mm. In this embodiment, the calculation sequence and calculation results of the observation notebook of the measuring station 1 are as follows: Figure 6 shown.

[0082] S3 Observation Book Output. Based on the observation records calculated in S2, a complete observation book is obtained in accordance with the standard format. On this basis, key calculation fields are randomly left blank and the leveling measurement observation record table is output, such as Figure 7 shown.

[0083] S4 users calculate and fill in the leveling observation record form.

[0084] The S5 system automatically checks and scores the leveling observation record sheets uploaded by users.

Claims

1. A leveling measurement example generation method and teaching auxiliary system, characterized in that: The specific features of the method for generating distance and height difference observation records for each measurement round are as follows: S1 obtains the distance d between each measuring section on the leveling route i and height difference h i , and the length L of the leveling route. S2 randomly generates the sight distance difference ΔS of each measuring station within the specification limit i , and calculate the cumulative difference in sight distance before and after any station S i (Unit: m), S i It should meet the tolerance requirements of each level measurement in the specification, see formula (1): S i =∑ΔS i (1) S3 is based on the distance d of each measuring section i , front and rear sight distance difference ΔS i , calculate the backsight distance D of each measuring station Bi and front sight distance D Fi (Unit: m), D Bi 、D Fi The tolerance requirements of each level measurement in the specification should be met, see formulas (2) and (3): S4 randomly generates the backsight lower wire reading R at each measuring station BLi , calculate the back sight upper wire reading R BUi (Unit: mm) (To simulate the actual observation process, the readings of the upper, middle and lower wires of the level instrument can meet the specification requirements. If the height difference h' of a certain measuring station j >0, then R BLi The value range is (0.5+h′ i )~(1+h′ i ); if the height difference of the measuring station is h′ j <0, then R BLi The value range is (2-h′ i )~(2.5-h′ i ) between) see formula (4): R BUi =R BLi +D Bi ×1000 (4) S5 randomly generates the difference α between the average value of the upper and lower wire readings and the middle wire reading within the specification limit Bi Calculate the backsight reading R of each station's basic division PBMi (Unit: mm), see formula (5): S6 randomly generates the difference β of the height difference measured by the Kiev division within the standard limit i , calculate the basic division height difference h of each measuring station Pi and the height difference of the auxiliary scale h Ai , that is, the value of the wire reading in the rear sight minus the value of the wire reading in the front sight (unit: mm), see formula (6) and (7): S7 calculates the front sight middle wire reading R of the basic scale at each measuring station PFMi (Unit: mm), see formula (8): R PFMi =R PBMi -h Pi (8) S8 randomly generates the difference α between the average value of the upper and lower wire readings and the middle wire reading within the specification limit Fi , calculate the front sight wire reading R of each measuring station FUi and the forward sight wire reading R FLi (Unit: mm), see formulas (9) and (10): S9 randomly generates the difference between the backsight Kiev scale readings γ Bi , calculate the difference γ between the Kiev scale readings of the front sight distance at each measuring station Fi (Unit: mm), γ Fi It should meet the tolerance requirements of each level measurement in the specification, see formula (11): c Fi =c Bi -b i (11) S10 generates the Kiev scale value K and calculates the middle wire reading R of the backsight auxiliary scale at each measuring station ABMi , see formula (12), the front sight auxiliary scale middle wire reading R AFMi The calculation method is the same as R ABMi (Unit: mm). R ABMi =R PBMi +K-γ Bi 。 (12) 2. A leveling measurement example generation method and teaching auxiliary system, characterized in that: The specific features of the method for generating a leveling route example are as follows: S1 obtains the elevation H of n leveling points on the leveling route j (j=1,2……n) and the distance d of each measuring section i (i=1,2……n-1), calculate the theoretical height difference h′ of each measuring section i (unit: m; i = 1, 2 ... n-1) and the length of the leveling route L (unit: km), see formulas (13) and (14): h′ i =H j+1 -H j (13) L=(∑d i ) / 1000 (14) S2 randomly generates the specification limit error and line closure error f h , taking the length of each station section as the weight, f h Assign to each measuring station and calculate the "observed" height difference h of each measuring station i (Unit: mm), see formula (15): S3 randomly generates various correction coefficients within the specification limits and calculates various correction values, including the normal level surface non-parallelism correction ε and the level rod length correction δ. Among them, the first and second class leveling measurements should also calculate the level rod temperature correction а, the gravity anomaly correction λ and the solid tide correction υ, and add the above correction values ​​to the leveling line (the above corrections may not be made in surveying teaching and engineering surveying competition training). S4 randomly generates the round trip height difference discrepancy value Δ within the specification limit, and calculates the accidental mean error M per kilometer of leveling measurement Δ , see formula (16), M Δ The specification tolerance requirements should be met. S5 distributes Δ evenly to the height difference between the forward and return measurement stations, see formulas (17) and (18) S6: Calculate the observation records of each measuring station for the forward and return measurements of the route according to the method of claim 1.

3. A leveling measurement example generation method and teaching auxiliary system, characterized in that: The closed loop leveling route calculation example generation method has the following specific features: S1 obtains the elevation H of n leveling points on the closed loop leveling route j (j=1,2……n) and the distance d of each measuring section i (i=1,2……n), calculate the theoretical height difference h′ of each measuring section i (unit: m; i = 1, 2...n) and the closed loop length F (unit: km), see formulas (19)-(21): h′ i =H j+1 -H j (i=1,2……n-1) (19) h′ n =H1-H n (20) F=(∑d i ) / 1000 (21) S2 randomly generates the inner loop closure error W within the specified tolerance limit, distributes W to each station with the length of the measuring section of each station as the weight, and calculates the "observed" height difference h of each station. i (Unit: mm), see formula (22): S3 calculates the observation records of each measuring station of the closed loop leveling route according to the method described in S3-S6 of claim 2.

4. A leveling measurement example generation method and teaching auxiliary system, characterized in that: A method for generating a leveling network example with more than 20 leveling rings, the specific features of which are as described in claim 3, except that after completing the calculation of the ring closure error W, it is also necessary to calculate the total mean error M per kilometer of leveling measurement. W , see formula (1), M W The specification tolerance requirements should be met. Where: W is the leveling ring closure error (unit: mm), F is the circumference of the leveling ring (unit: km), and N is the number of leveling rings.

5. A leveling measurement example generation method and teaching auxiliary system, characterized in that: The teaching auxiliary system is built and implemented, with the following specific features: S1 Leveling Route Design Module S1.1 Leveling route input. Supports importing leveling point results data, including .shp, .dwg, .txt and other formats, and visually displays the read leveling routes. S1.2 Leveling route adjustment. Dynamically configure the leveling route grade, route form (conformal / closed / node network), and observation instrument type. Perform coordinate translation and elevation adjustments manually or automatically to generate a variety of leveling route maps that meet regulatory tolerances. S2 observation and recording simulation module. Based on the calculation example generation method described in claims 1-4, and in accordance with the constraints of the technical indicators of the specifications, a complete observation data set with random errors is generated through reverse deduction of height difference and distance, observation value simulation and error simulation, including the sight distance, height difference, upper and lower wire readings and Kiev scale readings of each measuring station. The S3 notebook custom output module generates an observation dataset simulated in S2 according to the standard format of the leveling notebook. Key fields such as "Sight Distance Difference," "Kiev Differentiation Difference," and "Height Difference" are randomly left blank. The output includes a practice notebook containing the closure error allocation process and a complete derivation of the full mean error calculation steps. The S4 intelligent scoring and feedback module analyzes student calculation notebooks according to the level measurement test rules, compares the correctness of each cell in the notebook, marks cells with calculation errors, and provides instant scoring.

6. The teaching auxiliary system according to the above system claim is characterized in that: In the leveling route design module, the route form also includes a leveling network with more than 20 leveling rings, and when generating the route, the tolerance requirements of the corresponding level leveling measurement must be met, such as the accumulation of sight distance difference, closure difference, etc.

7. The teaching auxiliary system according to the above system claim is characterized in that: In the observation and recording simulation module, the random error simulation includes: Randomly generate error parameters such as sight distance difference, Kiev scale height difference, closure difference, etc. within the specification limit; The closure error is distributed according to the weight of the measuring section length, and the round-trip height difference and various correction values ​​(such as correction for non-parallelism of the normal level surface, correction for the length of the level rod, etc.) are calculated.

8. The teaching auxiliary system according to the above system claim is characterized in that: In the notebook customization output module, the format of the exercise notebook complies with the requirements of the "National Leveling Measurement Specifications", and the type and number of blank fields can be customized to adapt to the needs of different teaching stages.

9. The teaching auxiliary system according to the above system claim is characterized in that: In the intelligent scoring and feedback module, the detection rules include: Limit calibration of sight distance difference and cumulative difference; Correctness verification of the Kiev scale reading difference and height difference calculation; Normative verification of closure error distribution and mean error calculation.

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