CN109099877A - Space Cylindricity error evaluation based on longicorn palpus searching algorithm - Google Patents

Space Cylindricity error evaluation based on longicorn palpus searching algorithm Download PDF

Info

Publication number
CN109099877A
CN109099877A CN201810699923.9A CN201810699923A CN109099877A CN 109099877 A CN109099877 A CN 109099877A CN 201810699923 A CN201810699923 A CN 201810699923A CN 109099877 A CN109099877 A CN 109099877A
Authority
CN
China
Prior art keywords
longicorn
space
cylindricity
palpus
searching algorithm
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201810699923.9A
Other languages
Chinese (zh)
Inventor
王宸
付春才
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hubei University of Automotive Technology
Original Assignee
Hubei University of Automotive Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hubei University of Automotive Technology filed Critical Hubei University of Automotive Technology
Priority to CN201810699923.9A priority Critical patent/CN109099877A/en
Publication of CN109099877A publication Critical patent/CN109099877A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B21/00Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
    • G01B21/20Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring contours or curvatures, e.g. determining profile
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/15Correlation function computation including computation of convolution operations

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Computational Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Algebra (AREA)
  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Computing Systems (AREA)
  • Length Measuring Devices With Unspecified Measuring Means (AREA)
  • Image Analysis (AREA)

Abstract

The invention discloses the space Cylindricity error evaluations based on longicorn palpus searching algorithm, it is characterised in that it is the following steps are included: step 1: determining tested part, passes through the space line measurement data that three coordinate measuring machine obtains part;Step 2: establishing the error evaluation mathematical model of space linearity;Step 3: reading measuring point data, be brought into the error evaluation mathematical model of space linearity, longicorn palpus searching algorithm is initialized;Step 4: longicorn must searching algorithm iterative solution;Step 5: judge termination condition, judge whether the number of iterations meets maximum number of iterations, is terminated if it is satisfied, then calculating, if do not met, return step 4;Step 6: the fitness function value after iteration ends is the Spatial Straightness Error of measuring point.Simplify and solve process, improves the evaluating precision of Spatial Straightness Error.

Description

Space Cylindricity error evaluation based on longicorn palpus searching algorithm
Technical field
The present invention relates to the space Cylindricity error evaluations based on longicorn palpus searching algorithm, belong to component of machine essence Spend assessment method field.
Background technique
Due to the continuous development of Precision Manufacturing Technology, the digitized measurement of part has become the pass in product lifecycle Key step.In the rated element of part, space cylindricity is as tubing, a crucial morpheme of axial workpiece equal error evaluation Element, the accuracy of evaluation result can largely influence the evaluation result of part entirety.In relevant international mark In quasi- and national standard, the main algorithm of Cylindricity Error Evaluation is minimum area method, least square method and intelligent optimization algorithm Deng.Intelligent optimization algorithm such as ant group algorithm, particle swarm algorithm have been applied in the Cylindricity Error Evaluation problem of space more Extensively.But these algorithm effects and algorithm parameter choice relation are larger, and calculating speed is slower, and precision is not high enough, algorithm robust Property need further strengthen.Therefore the measuring point data that can be obtained by measuring tools such as three coordinates, acquires higher space cylinder The evaluating precision of degree is an important research direction of mechanical field of precision measurement.
Longicorn must searching algorithm be that principle of being looked for food according to longicorn designs.Longicorn has two long hairs, if left side food gas Taste is greater than the right, then longicorn is just turned left winged in next step, and vice versa.Food odors are set as function, two palpuses of longicorn by us Two o'clock odour value nearby can be acquired, the purpose of longicorn is to find the maximum point of global odour value, we copy longicorn behavior to set It counts intelligent optimization algorithm and carries out efficient function optimizing.
The defect and deficiency of the prior art:
(1) existing intelligent algorithm process is complicated, and late convergence is slower, is easily trapped into local optimum;
(2) algorithm solution room cylindricity trueness error is general;
(3) algorithm robustness is general.
Summary of the invention
It is the problems such as the complexity of process existing for existing space cylindricity assessment technology and excessively slow convergence rate, of the invention It is designed to provide a kind of space cylindricity assessment method based on longicorn palpus searching algorithm, process is solved to simplify, improves The evaluating precision of space cylindricity error.
In order to realize above-mentioned technical characteristic, the object of the present invention is achieved like this: based on longicorn palpus searching algorithm Space Cylindricity error evaluation, it the following steps are included:
Step 1: determining tested part, the space cylinder measurement data of part is obtained by three coordinate measuring machine;
Step 2: establishing the error evaluation mathematical model of space cylindricity;
Step 3: reading measuring point data, be brought into the error evaluation mathematical model of space cylindricity, calculation must be searched for longicorn Method is initialized;
Step 4: longicorn must searching algorithm iterative solution;
Step 5: judging termination condition, judge whether the number of iterations meets maximum number of iterations, if it is satisfied, then calculating eventually Only, if do not met, return step 4;
Step 6: the fitness function value after iteration ends is the space cylindricity error of measuring point.
The space cylindricity is departure of the cylinder relative to ideal cylinder, that is, contains the smallest cylinder of all measuring points, The error evaluation mathematical model establishment process of space cylindricity in the step 2 are as follows:
Establish space cylindricity ideal axis expression formula to be evaluated:
In formula: (l, m, n) is cylinder axis direction to be evaluated;
(x0,y0,z0) for normal, to be crossed with (l, m, n), coordinate origin makees plane and cylinder axis to be measured is formed by friendship Point;
(x, y, z) is actual point;
Random measuring point Pi(xi,yi,zi), (wherein i=1,2...k0,k0For measuring point number) arrive cylindricity to be measured desired axis Linear distance formula:
In formula: Pi(xi,yi,zi) it is random measuring point;
riFor PiTo the ideal axis distance of cylindricity to be measured;
A=(yi-y0)×n-(zi-z0)×m;
B=(zi-z0)×l-(xi-x0)×n;
C=(xi-x0)×m-(yi-y0)×l;
Measuring point is the semidiameter of two coaxial circles cylinders, i.e. target to the minimum range of ideal axis and the difference of maximum distance Function are as follows:
F=min (max (ri)-min(ri)) (3)
In formula: f is objective function.
The searching algorithm initialization of longicorn palpus specifically includes following parameter setting: variable step parameter Eta, day in the step 3 Distance d0 between two palpus of ox, longicorn step-length step, the number of iterations n, constant c, problem dimension D, random initial solution x=rands (D, 1), in formula: x is the random starting values in D-1;Rands is random function.
Longicorn palpus searching algorithm iterative process in the step 4 are as follows:
Calculate the left palpus coordinate of longicorn are as follows:
XL=x+d0*dir/2 (4)
Calculate the right palpus coordinate of longicorn are as follows:
XR=x-d0*dir/2 (5)
In formula: dir=rands (D, 1);Dir is the random value in D-1;d0The distance between two palpus of longicorn;X is random first Begin solution;
Calculate the odour intensity of the left palpus of longicorn, i.e. function fitness value:
Fleft=f (XL) (6)
Calculate the odour intensity of the right palpus of longicorn, i.e. function fitness value:
Fright=f (XR) (7)
The longicorn position to be walked in next step is calculated using step length changing method:
Compared with assessment technology before, the present invention has the advantages that
1, the space circle column parameter equation of design ideal, intuitively reflects the solution mathematical model of space cylindricity, does not have There are the cumbersome modeling process such as coordinate transformation process and the measuring point preprocessing process in minimum area method or least square method, it can be with Surveyed data adequately are applied to, and can be applied among a large amount of measuring point data.
2, in algorithm design aspect, longicorn palpus searching algorithm is designed, algorithm flow is simple, and operand is small, and convergence rate is more Fastly, there is stronger global optimizing ability, it is easy to accomplish.Solution procedure complies fully with the Minimum Area principle in international standard, Computational solution precision is higher.
Detailed description of the invention
Present invention will be further explained below with reference to the attached drawings and examples.
Fig. 1 is measurement model schematic diagram of the invention.
Fig. 2 is algorithm iteration curve graph of the invention.
Fig. 3 is flow chart of the invention.
Specific embodiment
Embodiments of the present invention are described further with reference to the accompanying drawing.
Embodiment 1:
As shown in Figure 1-3, the space Cylindricity error evaluation based on longicorn palpus searching algorithm, it includes following step It is rapid:
Step 1: determining tested part, the space cylinder measurement data of part is obtained by three coordinate measuring machine;
Step 2: establishing the error evaluation mathematical model of space cylindricity;
Step 3: reading measuring point data, be brought into the error evaluation mathematical model of space cylindricity, calculation must be searched for longicorn Method is initialized;
Step 4: longicorn must searching algorithm iterative solution;
Step 5: judging termination condition, judge whether the number of iterations meets maximum number of iterations, if it is satisfied, then calculating eventually Only, if do not met, return step 4;
Step 6: the fitness function value after iteration ends is the space cylindricity error of measuring point.
The space cylindricity is departure of the cylinder relative to ideal cylinder, that is, contains the smallest cylinder of all measuring points, The error evaluation mathematical model establishment process of space cylindricity in the step 2 are as follows:
Establish space cylindricity ideal axis expression formula to be evaluated:
In formula: (l, m, n) is cylinder axis direction to be evaluated;
(x0,y0,z0) for normal, to be crossed with (l, m, n), coordinate origin makees plane and cylinder axis to be measured is formed by friendship Point;
(x, y, z) is actual point;
Random measuring point Pi(xi,yi,zi), (wherein i=1,2...k0,k0For measuring point number) arrive cylindricity to be measured desired axis Linear distance formula:
In formula: Pi(xi,yi,zi) it is random measuring point;
riFor PiTo the ideal axis distance of cylindricity to be measured;
A=(yi-y0)×n-(zi-z0)×m;
B=(zi-z0)×l-(xi-x0)×n;
C=(xi-x0)×m-(yi-y0)×l;
Measuring point is the semidiameter of two coaxial circles cylinders, i.e. target to the minimum range of ideal axis and the difference of maximum distance Function are as follows:
F=min (max (ri)-min(ri)) (3)
In formula: f is objective function.
The searching algorithm initialization of longicorn palpus specifically includes following parameter setting: variable step parameter Eta, day in the step 3 Distance d0 between two palpus of ox, longicorn step-length step, the number of iterations n, problem dimension D, random initial solution x=rands (D, 1), in formula: X is the random starting values in D-1;Rands is random function.
Longicorn palpus searching algorithm iterative process in the step 4 are as follows:
Calculate the left palpus coordinate of longicorn are as follows:
XL=x+d0*dir/2 (4)
Calculate the right palpus coordinate of longicorn are as follows:
XR=x-d0*dir/2 (5)
In formula: dir=rands (D, 1);Dir is the random value in D-1;d0The distance between two palpus of longicorn;X is random first Begin solution;
Calculate the odour intensity of the left palpus of longicorn, i.e. function fitness value:
Fleft=f (XL) (6)
Calculate the odour intensity of the right palpus of longicorn, i.e. function fitness value:
Fright=f (XR) (7)
The longicorn position to be walked in next step is calculated using step length changing method:
Embodiment 2:
Based on longicorn must searching algorithm space Cylindricity error evaluation, it is characterised in that it the following steps are included:
Step 1: determining tested part, the space cylinder measurement data of part is obtained by three coordinate measuring machine;Space circle Column degree is actually departure of the cylinder relative to ideal cylinder, that is, contains the smallest cylinder of all measuring points.As shown in Figure 1
Step 2: establishing the error evaluation mathematical model of space cylindricity, detailed process are as follows:
Establish space cylindricity ideal axis expression formula to be evaluated:
In formula: (l, m, n) is cylinder axis direction to be evaluated;
(x0,y0,z0) for normal, to be crossed with (l, m, n), coordinate origin makees plane and cylinder axis to be measured is formed by friendship Point;
(x, y, z) is actual point;
Random measuring point Pi(xi,yi,zi), (wherein i=1,2...k0,k0For measuring point number) arrive cylindricity to be measured desired axis Linear distance formula:
In formula: Pi(xi,yi,zi) it is random measuring point;
riFor PiTo the ideal axis distance of cylindricity to be measured;
A=(yi-y0)×n-(zi-z0)×m;
B=(zi-z0)×l-(xi-x0)×n;
C=(xi-x0)×m-(yi-y0)×l;
Measuring point is the semidiameter of two coaxial circles cylinders, i.e. target to the minimum range of ideal axis and the difference of maximum distance Function are as follows:
F=min (max (ri)-min(ri)) (3)
In formula: f is objective function.
Step 3: reading measuring point data and the error evaluation mathematical model of space cylindricity is brought into, to day as shown in table 1 Ox palpus searching algorithm is initialized;Specifically include following parameter setting: variable step parameter Eta, distance d0 between two palpus of longicorn, day Ox step-length step, constant c, the number of iterations n, problem dimension D, random initial solution x=rands (D, 1), in formula: x is in D-1 Random starting values;Rands is random function, enters step 4;
1 cylindricity measurement point coordinate of table
Initiation parameter in the present embodiment:
Wherein: Eta=0.95, c=5, n=20, D=20, step=1;
Step1=Eta*step, d0=step1/c,
Step 4: longicorn palpus searching algorithm iterative solution, specific iterative process are as follows:
Calculate the left palpus coordinate of longicorn are as follows:
XL=x+d0*dir/2 (4)
Calculate the right palpus coordinate of longicorn are as follows:
XR=x-d0*dir/2 (5)
In formula: dir=rands (D, 1);Dir is the random value in D-1;d0The distance between two palpus of longicorn;X is random first Begin solution;
Calculate the odour intensity of the left palpus of longicorn, i.e. function fitness value:
Fleft=f (XL) (6)
Calculate the odour intensity of the right palpus of longicorn, i.e. function fitness value:
Fright=f (XR) (7)
The longicorn position to be walked in next step is calculated using step length changing method:
Step 5: judging termination condition, judge whether the number of iterations meets maximum number of iterations, if it is satisfied, then calculating eventually Only, if do not met, return step 4;
Step 6: the fitness function value after iteration ends is the space cylindricity error of measuring point.Position coordinates are to meet The solution of objective function (3), the i.e. equation parameter of space cylinder.Iterativecurve is as shown in Figure 2.
The analysis of arithmetic result:
According to the measuring point data of reading, in algorithm iteration calculating process, when iterating to 80 times, just reach convergence, Convergence rate is improved;Calculated space cylindricity error amount is 0.00192mm.Space cylindricity error precision is mentioned It is high.
Above-described embodiment is used to illustrate the present invention, rather than limits the invention, in spirit of the invention and In scope of protection of the claims, to any modifications and changes that the present invention makes, protection scope of the present invention is both fallen within.

Claims (4)

1. based on longicorn must searching algorithm space Cylindricity error evaluation, it is characterised in that it the following steps are included:
Step 1: determining tested part, the space cylinder measurement data of part is obtained by three coordinate measuring machine;
Step 2: establishing the error evaluation mathematical model of space cylindricity;
Step 3: read measuring point data, be brought into the error evaluation mathematical model of space cylindricity, to longicorn must searching algorithm into Row initialization;
Step 4: longicorn must searching algorithm iterative solution;
Step 5: judge termination condition, judge whether the number of iterations meets maximum number of iterations, is terminated if it is satisfied, then calculating, If do not met, return step 4;
Step 6: the fitness function value after iteration ends is the space cylindricity error of measuring point.
2. the space Cylindricity error evaluation according to claim 1 based on longicorn palpus searching algorithm, feature exist In: space cylindricity is departure of the cylinder relative to ideal cylinder, that is, contains the smallest cylinder of all measuring points, the step 2 The error evaluation mathematical model establishment process of middle space cylindricity are as follows:
Establish space cylindricity ideal axis expression formula to be evaluated:
In formula: (l, m, n) is cylinder axis direction to be evaluated;
(x0,y0,z0) for normal, to be crossed with (l, m, n), coordinate origin makees plane and cylinder axis to be measured is formed by intersection point;
(x, y, z) is actual point;
Random measuring point Pi(xi,yi,zi), (wherein i=1,2...k0,k0For measuring point number) to cylindricity to be measured ideal axis away from From formula:
In formula: Pi(xi,yi,zi) it is random measuring point;
riFor PiTo the ideal axis distance of cylindricity to be measured;
A=(yi-y0)×n-(zi-z0)×m;
B=(zi-z0)×l-(xi-x0)×n;
C=(xi-x0)×m-(yi-y0)×l;
Measuring point is the semidiameter of two coaxial circles cylinders, i.e. objective function to the minimum range of ideal axis and the difference of maximum distance Are as follows:
F=min (max (ri)-min(ri)) (3)
In formula: f is objective function.
3. the space Cylindricity error evaluation according to claim 1 based on longicorn palpus searching algorithm, feature exist In: the searching algorithm initialization of longicorn palpus specifically includes following parameter setting: variable step parameter Eta, two palpus of longicorn in the step 3 Between distance d0, longicorn step-length step, constant c, the number of iterations n, problem dimension D, random initial solution x=rands (D, 1), in formula: X is the random starting values in D-1;Rands is random function.
4. the space Cylindricity error evaluation according to claim 1 based on longicorn palpus searching algorithm, feature exist In: longicorn palpus searching algorithm iterative process in the step 4 are as follows:
Calculate the left palpus coordinate of longicorn are as follows:
XL=x+d0*dir/2 (4)
Calculate the right palpus coordinate of longicorn are as follows:
XR=x-d0*dir/2 (5)
In formula: dir=rands (D, 1);Dir is the random value in D-1;d0The distance between two palpus of longicorn;X is random initial solution;
Calculate the odour intensity of the left palpus of longicorn, i.e. function fitness value:
Fleft=f (XL) (6)
Calculate the odour intensity of the right palpus of longicorn, i.e. function fitness value:
Fright=f (XR) (7)
The longicorn position to be walked in next step is calculated using step length changing method:
CN201810699923.9A 2018-06-29 2018-06-29 Space Cylindricity error evaluation based on longicorn palpus searching algorithm Pending CN109099877A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810699923.9A CN109099877A (en) 2018-06-29 2018-06-29 Space Cylindricity error evaluation based on longicorn palpus searching algorithm

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810699923.9A CN109099877A (en) 2018-06-29 2018-06-29 Space Cylindricity error evaluation based on longicorn palpus searching algorithm

Publications (1)

Publication Number Publication Date
CN109099877A true CN109099877A (en) 2018-12-28

Family

ID=64845201

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810699923.9A Pending CN109099877A (en) 2018-06-29 2018-06-29 Space Cylindricity error evaluation based on longicorn palpus searching algorithm

Country Status (1)

Country Link
CN (1) CN109099877A (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109756910A (en) * 2019-01-02 2019-05-14 河海大学 Based on the unmanned plane network resource allocation method for improving longicorn palpus searching algorithm
CN115096243A (en) * 2022-06-14 2022-09-23 哈尔滨工业大学 Standard device coaxiality measuring method for searching optimal rotating shaft through cloud adaptive genetic algorithm
CN115371623A (en) * 2022-08-25 2022-11-22 重庆大学 Improved sparrow optimization algorithm-based axis straightness error evaluation method and system

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100106455A1 (en) * 2008-10-29 2010-04-29 Sumitomo Heavy Industries, Ltd. Straightness measuring method and straightness measuring apparatus
CN102982240A (en) * 2012-11-19 2013-03-20 华侨大学 Roundness error evaluation method based on variable-metric chaotic simulated annealing algorithm
CN106885514A (en) * 2017-02-28 2017-06-23 西南科技大学 A kind of Deep Water Drilling Riser automatic butt position and posture detection method based on machine vision
CN107330550A (en) * 2017-06-23 2017-11-07 湖北汽车工业学院 Space cylindricity assessment method based on double annealing learning aid algorithm

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100106455A1 (en) * 2008-10-29 2010-04-29 Sumitomo Heavy Industries, Ltd. Straightness measuring method and straightness measuring apparatus
CN102982240A (en) * 2012-11-19 2013-03-20 华侨大学 Roundness error evaluation method based on variable-metric chaotic simulated annealing algorithm
CN106885514A (en) * 2017-02-28 2017-06-23 西南科技大学 A kind of Deep Water Drilling Riser automatic butt position and posture detection method based on machine vision
CN107330550A (en) * 2017-06-23 2017-11-07 湖北汽车工业学院 Space cylindricity assessment method based on double annealing learning aid algorithm

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
LISHUAI8: "《知乎,https://zhuanlan.zhihu.com/p/30742461》", 4 November 2017 *

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109756910A (en) * 2019-01-02 2019-05-14 河海大学 Based on the unmanned plane network resource allocation method for improving longicorn palpus searching algorithm
CN109756910B (en) * 2019-01-02 2020-07-14 河海大学 Unmanned aerial vehicle network resource allocation method based on improved longicorn stigma search algorithm
CN115096243A (en) * 2022-06-14 2022-09-23 哈尔滨工业大学 Standard device coaxiality measuring method for searching optimal rotating shaft through cloud adaptive genetic algorithm
CN115096243B (en) * 2022-06-14 2023-08-18 哈尔滨工业大学 Standard coaxiality measuring method for searching optimal rotating shaft by cloud adaptation genetic algorithm
CN115371623A (en) * 2022-08-25 2022-11-22 重庆大学 Improved sparrow optimization algorithm-based axis straightness error evaluation method and system

Similar Documents

Publication Publication Date Title
CN108319764A (en) Evaluation method for spatial straightness errors method based on longicorn palpus searching algorithm
CN106023298B (en) Point cloud Rigid Registration method based on local Poisson curve reestablishing
CN109099877A (en) Space Cylindricity error evaluation based on longicorn palpus searching algorithm
CN104482911B (en) Sphericity error assessment method based on error ball
CN106248035A (en) The method and system that a kind of surface profile based on point cloud model accurately detects
CN108182433A (en) A kind of meter reading recognition methods and system
US9852360B2 (en) Data clustering apparatus and method
CN103942837B (en) The direct building method of blade point cloud model cross section curve based on Successive linear programming
CN108871256B (en) Roundness error evaluation algorithm
CN109141266B (en) Steel structure measuring method and system
CN103869279B (en) Multi-target positioning tracking method with multiple sensor platforms
CN112904139A (en) High-voltage switch cabinet partial discharge positioning method and system considering temperature field change
CN108332685B (en) A kind of coding structural light three-dimensional measurement method
CN103278126A (en) Sphericity error assessment method for part based on minimum area
CN105389800B (en) Row parameter object method of estimation
CN104990501A (en) Three-dimensional laser scanning device system parameter calibration method
CN114428809A (en) Method and device for obtaining accuracy of map data and computer equipment
CN105157655A (en) Roundness error quick evaluation method based on regional search
CN103292654A (en) Method for calculating function size of cylindrical part
CN106643629A (en) Tubular structure inner surface roughness measurement calculating method
Di Angelo et al. A robust method for axis identification
CN104391272B (en) The method and system of target positioning is carried out using direction finding data
CN105678229A (en) High spectral image retrieval method
CN109508482A (en) A kind of calculation method for complex-curved surface profile degree error uncertainty
Casaer et al. Analysing space use patterns by Thiessen polygon and triangulated irregular network interpolation: a non-parametric method for processing telemetric animal fixes

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20181228

RJ01 Rejection of invention patent application after publication