CN106872579B - Normal distribution is fitted the method that rock mass velocity divides rock-mass quality classification - Google Patents
Normal distribution is fitted the method that rock mass velocity divides rock-mass quality classification Download PDFInfo
- Publication number
- CN106872579B CN106872579B CN201710075731.6A CN201710075731A CN106872579B CN 106872579 B CN106872579 B CN 106872579B CN 201710075731 A CN201710075731 A CN 201710075731A CN 106872579 B CN106872579 B CN 106872579B
- Authority
- CN
- China
- Prior art keywords
- velocity
- rock mass
- rock
- wave
- normpdf
- 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.)
- Active
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
- G01N29/07—Analysing solids by measuring propagation velocity or propagation time of acoustic waves
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2291/00—Indexing codes associated with group G01N29/00
- G01N2291/02—Indexing codes associated with the analysed material
- G01N2291/023—Solids
- G01N2291/0232—Glass, ceramics, concrete or stone
Landscapes
- Physics & Mathematics (AREA)
- Acoustics & Sound (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Or Analyzing Materials By The Use Of Ultrasonic Waves (AREA)
- Investigation Of Foundation Soil And Reinforcement Of Foundation Soil By Compacting Or Drainage (AREA)
Abstract
The present invention provides a kind of normal distribution method that fitting rock mass velocity divides rock-mass quality classification, includes the following steps: Step 1: by the rock mass velocity data of actual measurement by sorting from small to large, and count the number of each velocity of wave data, velocity of wave data probability is normalized；Step 2: obtaining rock mass velocity data model function using the velocity of wave data after normpdf Fitted probability normalization under least square method；Step 3: being the characteristic of inflection point at x=μ ± σ using normpdf f (x, μ, σ) curve, with x=μ in rock mass velocity data model function F (x)i±σiAs rock mass classification standard value, rock mass classification is carried out using rock mass velocity data model function F (x) expected value, standard deviation.The present invention recycles normpdf in statistics to divide divide rock-mass quality classification, can reduce building-site test work load, significantly improve work efficiency only according to work area rock mass velocity value.
Description
Technical field
The present invention relates to engineering investigations to design engineering investigation design field, and specifically a kind of normal distribution is fitted rock mass
The method of velocity of wave division rock-mass quality classification.
Background technique
At present in terms of dividing rock-mass quality classification, it is equal that the every profession and trades such as existing water conservancy, electric power, highway, railway reconnoitre field
Algorithm without specific, concrete, at present every profession and trade regulation, specification be all made of rock mass hardness (hard rock, compared with hard rock, compared with soft rock,
Soft rock, ultimate soft rock) it divides with rock mass completeness (complete, more complete, relatively broken, broken, smashed to pieces) list corresponded manner
Rock-mass quality classification.In real work, rock-mass quality classification divide generally according to laboratory sillar test result (compression strength,
Velocity of wave), the data such as live wave velocity testing divide in conjunction with empirical value.Existing outstanding problem is that calculation method is indefinite, mixes
Miscellaneous personal experience, grade scale value inaccuracy, the defects of work area actual conditions specific aim is not strong.
Summary of the invention
The object of the present invention is to provide a kind of relatively accurate, more targetedly rock mass matter for being more suitable for engineering investigation design
Measure rank calculation methods, i.e., only according to work area rock mass velocity value, recycle in statistics normpdf come into
Row divides rock-mass quality classification and divides.
The technical scheme of the present invention is realized as follows:
A kind of method that normal distribution fitting rock mass velocity divides rock-mass quality classification, includes the following steps:
Step 1: by the rock mass velocity data of actual measurement by sorting from small to large, and the number of each velocity of wave data is counted, by wave
Fast data probability normalization:
In above formula: n represents the quantity of different rock mass velocity values after sequencing statistical；
VpiRepresent i-th of rock mass velocity value；
NiRepresent the number of i-th of rock mass velocity value；
S represents area between velocity of wave data and curves and abscissa line；
DiRepresent the probability density of velocity of wave data after probability normalizes；
Step 2: (determining that normal distribution is general according to practical feelings using normpdf under least square method
Rate density function number, same work area, with 1 to 2 normpdf, complex situations in the case where same lithology
Under can use 3 or more normpdfs)
Velocity of wave data after Fitted probability normalization, obtain rock mass velocity data model function:
In above formula: n represents normpdf quantity；
λiRepresent i-th of normpdf weight, λi>=0 and ∑ λi=1；
μiRepresent i-th of normpdf expected value；
σiIt is poor to represent i-th of normpdf Plays；
Step 3: be the characteristic of inflection point at x=μ ± σ using normpdf f (x, μ, σ) curve,
With x=μ in rock mass velocity data model function F (x)i±σiAs rock mass classification standard value, rock mass velocity data model letter is utilized
Number F (x) expected value, standard deviation carry out rock mass classification.Classification basic principle is, when velocity of wave is suitble to single normal distribution probability close
When spending function curve fitting, μ+σ value is greater than with velocity of wave and is divided into the first order；It is greater than μ-σ with velocity of wave and is less than μ+σ value and is divided into the
Second level；It is less than μ-σ value with velocity of wave and is divided into the third level.When velocity of wave is suitble to two normpdf curve matchings
When, it is averaged at two curve adjacent comers as cut off value, other are constant.
Further, basic principle is classified in step 3 are as follows: when velocity of wave is suitble to single normpdf bent
When line is fitted, μ+σ value is greater than with velocity of wave and is divided into the first order；It is greater than μ-σ with velocity of wave and is less than μ+σ value and is divided into the second level；With
Velocity of wave is less than μ-σ value and is divided into the third level.
It further, further include that velocity of wave data should be carried out with pre-treatment step before step 2, rejecting is significantly isolated different
After constant value, then carry out normpdf fitting.
Further, the normpdf quantity view rock mass velocity statistic curve being fitted in step 2
Form medium wave peak number determines.
The invention has the advantages that
1. needing the value of wave speed of rock mass that can divide rock mass classification, other rock mass test parameters are not needed, to reduce
Building-site test work load, is remarkably improved work efficiency.
2. this method is established on the basis of mathematical statistics, the rock mass velocity value for participating in calculating is more, as a result more can really put
Reflect work area rock mass actual conditions.Increasing for the rock mass velocity value that the present invention can be calculated with participation, is corrected in time.
3. introducing weight λiThe desired value μ in pattern function in each normpdf can be reducediAnd standard
Poor σiIt interacts, such as when wave velocity testing data largely concentrate low velocity of wave area or high velocity of wave area, the model F (x) that is fitted
Function can be mainly reflected in weight λiVariation, and desired value μiAnd standard deviation sigmaiIt then varies less, keeps the standard of fitting result
True property.
4. practical simplicity calculates rapidly, easy to spread universal.By the practical application that multiple work areas carry out, as a result prove
The present invention be technically it is feasible, compare with additional fractionation method, calculate difference and be not more than 5%, and better reflect
The actual conditions of work area rock mass.
Detailed description of the invention
Fig. 1 is the rock mass velocity Data-Statistics figure surveyed in the embodiment of the present invention；
Fig. 2 is that normal distribution probability density curve is fitted rock mass velocity probability density curve figure in the embodiment of the present invention；
Fig. 3 is that normal distribution is fitted rock-mass quality classification schematic diagram in the embodiment of the present invention；
Fig. 4 is normal distribution fitting rock mass classification of the present invention and conventional rock mass classification comparison diagram, and wherein Fig. 4 (a) is conventional
Rock mass classification, Fig. 4 (b) are normal state fitting of distribution rock mass classification.
Specific embodiment
Below in conjunction with the attached drawing in the present invention, the technical solution in the present invention is clearly and completely described.
The present invention provides a kind of method that normal distribution fitting rock mass velocity divides rock-mass quality classification, including walks as follows
It is rapid:
Step 1: by the rock mass velocity data of actual measurement by sorting from small to large, and count the number of each velocity of wave data, such as table
Shown in 1, and rock mass velocity Data-Statistics figure is drawn, sees Fig. 1.
1 rock mass velocity Data-Statistics table of table
| Velocity of wave (m/s) | 2500 | 2530 | 2660 | 2730 | 2770 | 2810 | 2850 | 2890 | 2940 | 2980 | 3030 | 3070 |
| Quantity (a) | 1 | 1 | 1 | 1 | 4 | 5 | 6 | 7 | 3 | 13 | 11 | 27 |
| Velocity of wave (m/s) | 3120 | 3170 | 3220 | 3270 | 3330 | 3380 | 3440 | 3500 | 3570 | 3630 | 3700 | 3770 |
| Quantity (a) | 23 | 43 | 38 | 55 | 85 | 86 | 123 | 169 | 188 | 236 | 223 | 272 |
| Velocity of wave (m/s) | 3840 | 3920 | 4000 | 4080 | 4160 | 4250 | 4340 | 4440 | 4540 | 4650 | 4760 | 4870 |
| Quantity (a) | 257 | 251 | 195 | 264 | 270 | 269 | 275 | 299 | 330 | 404 | 379 | 429 |
| Velocity of wave (m/s) | 5000 | 5120 | 5260 | 5400 | 5550 | 5710 | ||||||
| Quantity (a) | 398 | 255 | 110 | 38 | 2 | 1 |
Velocity of wave data probability is normalized: i.e. using normalization formula, area between rock mass velocity value and abscissa line being returned
It is 1, draws rock mass velocity value probability density curve (rock mass velocity value probability density curve and rock mass velocity Data-Statistics tracing pattern
It is similar, be multiple proportion).
In above formula: n represents the quantity of different rock mass velocity values after sequencing statistical；
Vpi represents i-th of rock mass velocity value；
NiRepresent the number of i-th of rock mass velocity value；
S represents area between velocity of wave data and curves and abscissa line；
DiRepresent the probability density of velocity of wave data after probability normalizes；
Step 2: utilizing normpdf (normal distribution determines according to actual conditions under least square method
Probability density function number, same work area, with 1 to 2 normpdf, complicated feelings in the case where same lithology
3 or more normpdfs can be used under condition)
Velocity of wave data after Fitted probability normalization, obtain rock mass velocity data model function F (x) and parameters (λi、
μi、σi):
In above formula: n represents normpdf quantity；
λiRepresent i-th of normpdf weight, λi>=0 and ∑ λi=1；
μiRepresent i-th of normpdf expected value；
σiIt is poor to represent i-th of normpdf Plays；
Can velocity of wave data should also be carried out with pre-treatment step before executing step 2, reject significantly isolated exceptional value
Afterwards, then normpdf fitting is carried out.
Least square method, which is based on, using normpdf is fitted rock mass velocity value probability density curve such as Fig. 2
It is shown, in one embodiment, rock mass velocity data model function are as follows:
F (x)=0.46f (x, 3920,390)+(1-0.46) f (x, 4820,290)
Step 3: be the characteristic of inflection point at x=μ ± σ using normpdf f (x, μ, σ) curve,
With x=μ in rock mass velocity data model function F (x)i±σiAs rock mass classification standard value, rock mass velocity data model letter is utilized
Number F (x) expected value, standard deviation carry out rock mass classification.Classification basic principle is, when velocity of wave is suitble to single normal distribution probability close
When spending function curve fitting, μ+σ value is greater than with velocity of wave and is divided into the first order；It is greater than μ-σ with velocity of wave and is less than μ+σ value and is divided into the
Second level；It is less than μ-σ value with velocity of wave and is divided into the third level, as shown in Figure 3.When velocity of wave is suitble to two normpdfs
When curve matching, it is averaged at two curve adjacent comers as cut off value, other are constant.
This method classification is shown in Fig. 4 and table 2 with conventional method classification comparison.
2 rock mass classification Comparison of standards table of table
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
Belong to those skilled in the art in the technical scope disclosed by the present invention, any changes or substitutions that can be easily thought of, all answers
It is included within the scope of the present invention.Therefore, protection scope of the present invention should be subject to the protection scope in claims.
Claims (3)
1. a kind of method that normal distribution fitting rock mass velocity divides rock-mass quality classification, it is characterised in that include the following steps:
Step 1: by the rock mass velocity data of actual measurement by sorting from small to large, and the number of each velocity of wave data is counted, by velocity of wave number
It is normalized according to probability:
In above formula: n represents the quantity of different rock mass velocity values after sequencing statistical；
VpiRepresent i-th of rock mass velocity value；
NiRepresent the number of i-th of rock mass velocity value；
S represents area between velocity of wave data and curves and abscissa line；
DiRepresent the probability density of velocity of wave data after probability normalizes；
Step 2: utilizing normpdf under least square method
Velocity of wave data after Fitted probability normalization, obtain rock mass velocity data model function:
In above formula: n represents normpdf quantity；
λiRepresent i-th of normpdf weight, λi>=0 and ∑ λi=1；
μiRepresent i-th of normpdf expected value；
σiIt is poor to represent i-th of normpdf Plays；
Step 3: being the characteristic of inflection point at x=μ ± σ using normpdf f (x, μ, σ) curve, in rock mass
With x=μ in velocity of wave data model function F (x)i±σiAs rock mass classification standard value, rock mass velocity data model function F is utilized
(x) expected value, standard deviation carry out rock mass classification；
Basic principle is classified in step 3 are as follows: when velocity of wave is suitble to single normpdf curve matching, with wave
Speed is greater than μ+σ value and is divided into the first order；It is greater than μ-σ with velocity of wave and is less than μ+σ value and is divided into the second level；It is less than μ-σ value with velocity of wave
It is divided into the third level.
2. the method that normal distribution fitting rock mass velocity as described in claim 1 divides rock-mass quality classification, it is characterised in that:
Further include that velocity of wave data should be carried out with pre-treatment step before step 2, after rejecting significantly isolated exceptional value, then carries out normal state
The fitting of distribution probability density function.
3. the method that normal distribution fitting rock mass velocity as described in claim 1 divides rock-mass quality classification, it is characterised in that:
The normpdf quantity view rock mass velocity statistic curve form medium wave peak number being fitted in step 2 determines.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710075731.6A CN106872579B (en) | 2017-02-13 | 2017-02-13 | Normal distribution is fitted the method that rock mass velocity divides rock-mass quality classification |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710075731.6A CN106872579B (en) | 2017-02-13 | 2017-02-13 | Normal distribution is fitted the method that rock mass velocity divides rock-mass quality classification |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106872579A CN106872579A (en) | 2017-06-20 |
| CN106872579B true CN106872579B (en) | 2019-09-13 |
Family
ID=59165820
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710075731.6A Active CN106872579B (en) | 2017-02-13 | 2017-02-13 | Normal distribution is fitted the method that rock mass velocity divides rock-mass quality classification |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106872579B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110794039B (en) * | 2019-11-06 | 2021-12-21 | 长江勘测规划设计研究有限责任公司 | Method for calculating crack filling rate of curtain grouting rock mass by using rock mass wave velocity |
| CN113050169B (en) * | 2021-03-18 | 2021-11-05 | 长安大学 | Rock mass anisotropy coefficient probability analysis method based on Monte Carlo sampling |
| CN113657515B (en) * | 2021-08-20 | 2024-06-14 | 盾构及掘进技术国家重点实验室 | Classification method for judging and improving surrounding rock grade of FMC model tunnel based on rock opportunity sense parameters |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| ES2263307B1 (en) * | 2003-05-23 | 2007-09-16 | Asociacion De Investigacion De Industrias De La Construccion Aidico | PROCEDURE FOR QUALITY DIAGNOSIS, IN ORNAMENTAL ROCK BLOCKS OF LARGE DIMENSIONS AND DEVICES FOR PUTTING INTO PRACTICE. |
| CN106326620A (en) * | 2015-07-01 | 2017-01-11 | 中国石油化工股份有限公司 | Optimized selection method for diagenetic coefficient model of exploration target distribution range |
| CN106124632B (en) * | 2016-07-22 | 2018-05-15 | 山东大学 | A kind of concrete density appraisal procedure based on ultrasonic wave |
-
2017
- 2017-02-13 CN CN201710075731.6A patent/CN106872579B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN106872579A (en) | 2017-06-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106872579B (en) | Normal distribution is fitted the method that rock mass velocity divides rock-mass quality classification | |
| Davies et al. | Adaptive kernel estimation of spatial relative risk | |
| CN106371080B (en) | Radar target identification method based on geometry feature and combination features | |
| CN107967571A (en) | Index system generation method based on entropy assessment | |
| CN104112062B (en) | The acquisition methods of wind-resources distribution based on interpolation method | |
| Das et al. | Examination of homogeneity of selected Irish pooling groups | |
| CN109598015B (en) | Grading evaluation method for rock mass fragmentation degree of fragmentation structure | |
| CN107688863A (en) | The short-term wind speed high accuracy combination forecasting method that adaptive iteration is strengthened | |
| CN109030014A (en) | To the prediction technique of internal car noise subjective scoring when vehicle accelerates | |
| CN107194114B (en) | Method for calculating multi-fractal parameter of rock structural surface | |
| Doszyń | Statistical determination of impact of property attributes for weak measurement scales | |
| CN116050007A (en) | Complex equipment optimization design method based on hybrid self-adaptive sampling agent model | |
| CN102663684B (en) | SAR image segmentation method based on Gauss mixing model parameter block migration clustering | |
| CN105956318A (en) | Improved splitting H-K clustering method-based wind power plant fleet division method | |
| CN107292100B (en) | Method for calculating fractal dimension of rock structural surface | |
| CN107316503A (en) | A kind of congestion focus space domain sector recognition methods based on multistage matter-element entropy weight | |
| CN108898322A (en) | A kind of electric grid investment strategy benefit integrated evaluating method based on FCM algorithm | |
| CN107577896A (en) | Equivalence method is polymerize based on the theoretical wind power plant multimachines of mixing Copula | |
| CN109583003B (en) | Face-crack polygon-based method for quantifying cracking degree of cracked structure rock mass | |
| CN105718668A (en) | Open pit mine cast blasting effect analysis method | |
| CN115081298A (en) | Method for qualitatively and quantitatively characterizing and analyzing point set in three-dimensional space | |
| CN108335053A (en) | A kind of application study type military research Task application evaluation method | |
| CN108051676A (en) | A kind of amplitude of lightning current cumulative probability distribution curve the Fitting Calculation method | |
| CN112818439A (en) | Soft rock tunnel surrounding rock sub-grade grading method | |
| CN108923414B (en) | Coherent unit grouping method based on panel data weighted clustering |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |