CN106872579A - The method that normal distribution fitting rock mass velocity divides rock-mass quality classification - Google Patents

The method that normal distribution fitting rock mass velocity divides rock-mass quality classification Download PDF

Info

Publication number
CN106872579A
CN106872579A CN201710075731.6A CN201710075731A CN106872579A CN 106872579 A CN106872579 A CN 106872579A CN 201710075731 A CN201710075731 A CN 201710075731A CN 106872579 A CN106872579 A CN 106872579A
Authority
CN
China
Prior art keywords
velocity
rock mass
rock
normpdf
wave
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.)
Granted
Application number
CN201710075731.6A
Other languages
Chinese (zh)
Other versions
CN106872579B (en
Inventor
刘海涛
孙云志
蔡耀军
魏岩峻
董亮
徐复兴
吴蒙蒙
王军怀
彭军
熊友亮
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.)
Changjiang Institute of Survey Planning Design and Research Co Ltd
Original Assignee
Changjiang Institute of Survey Planning Design and Research Co Ltd
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 Changjiang Institute of Survey Planning Design and Research Co Ltd filed Critical Changjiang Institute of Survey Planning Design and Research Co Ltd
Priority to CN201710075731.6A priority Critical patent/CN106872579B/en
Publication of CN106872579A publication Critical patent/CN106872579A/en
Application granted granted Critical
Publication of CN106872579B publication Critical patent/CN106872579B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

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 method that normal distribution fitting rock mass velocity divides rock-mass quality classification, comprises the following steps：Step one, 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 the normalization of velocity of wave data probability；Step 2, using under least square method normpdf Fitted probability normalize after velocity of wave data, obtain rock mass velocity data model function；Step 3, using normpdf f (x, μ, σ) curves at x=μ ± σ for flex point characteristic, 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 in statistics normpdf and divides carrying out dividing rock-mass quality classification only according to work area rock mass velocity value, and it can reduce building-site experiment work amount, significantly improve work efficiency.

Description

The method that normal distribution fitting rock mass velocity divides rock-mass quality classification
Technical field
The present invention relates to engineering investigation design engineering investigation design field, specifically a kind of normal distribution fitting rock mass The method that velocity of wave divides rock-mass quality classification.
Background technology
At present in terms of rock-mass quality classification is divided, the every profession and trade such as existing water conservancy, electric power, highway, railway prospecting field is equal Algorithm without specific, concrete, current every profession and trade code, specification using rock mass hardness (hard rock, compared with hard rock, compared with soft rock, Soft rock, ultimate soft rock) divide 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 it is general 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.The outstanding problem of presence is that computational methods are indefinite, mixes Miscellaneous personal experience, the defect such as grade scale value is inaccurate, work area actual conditions specific aim is not strong.
The content of the invention
It is an object of the invention to provide a kind of relatively accurate, more targetedly rock mass matter for being more suitable for engineering investigation design Amount rank calculation methods, i.e., only according to work area rock mass velocity value, recycle in statistics normpdf to enter Row divides rock-mass quality classification and divides.
The technical proposal of the invention is realized in this way：
A kind of method that normal distribution fitting rock mass velocity divides rock-mass quality classification, comprises the following steps：
Step one, 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 ripple Fast data probability normalization：
In above formula：N represents the quantity of different rock mass velocity values after sequencing statistical；
VpiRepresent i-th rock mass velocity value；
NiRepresent i-th number 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 is normalized；
Step 2, (determine that normal distribution is general according to actual feelings using normpdf under least square method With 1 to 2 normpdf, complex situations in the case of rate density function number, same work area, same lithology Under can use more than 3 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 normpdf weight, λi>=0 and ∑ λi=1；
μiRepresent i-th normpdf expected value；
σiRepresent i-th normpdf Plays poor；
Step 3, using normpdf f (x, μ, σ) curves at x=μ ± σ for flex point characteristic, With x=μ in rock mass velocity data model function F (x)i±σiAs rock mass classification standard value, using rock mass velocity data model letter Number F (x) expected value, standard deviation carry out rock mass classification.Classification basic principle is, when the suitable wall scroll normal distribution probability of velocity of wave is close When degree function curve is fitted, the first order is divided into more than μ+σ values with velocity of wave；With velocity of wave the is divided into more than μ-σ and less than μ+σ values Two grades；The third level is divided into less than μ-σ values with velocity of wave.When velocity of wave is adapted to two normpdf curve matchings When, to be averaged as cut off value at two curve adjacent comers, other are constant.
Further, basic principle is classified in step 3 is：When velocity of wave is adapted to wall scroll normpdf song When line is fitted, the first order is divided into more than μ+σ values with velocity of wave；The second level is divided into more than μ-σ and less than μ+σ values with velocity of wave；With Velocity of wave is divided into the third level less than μ-σ values.
Further, also include that velocity of wave data should be carried out pre-treatment step before step 2, reject and significantly isolate different After constant value, then carry out normpdf fitting.
Further, the normpdf quantity being fitted in step 2 regards rock mass velocity statistic curve Form medium wave peak number determines.
It is an advantage of the invention that：
1. rock mass classification is divided by only needing to the value of wave speed of rock mass, it is not necessary to other rock mass test parameters, so as to reduce Building-site experiment work amount, is remarkably improved work efficiency.
2. this method is set up on the basis of mathematical statistics, and the rock mass velocity value for participating in calculating is more, as a result more can truly put Reflect work area rock mass actual conditions.The present invention can increasing with the rock mass velocity value for participating in calculating, in time amendment.
3. weight λ is introducediThe desired value μ in each normpdf in pattern function can be reducediAnd standard Difference σiInteract, such as when wave velocity testing data are most of concentrates low velocity of wave area or velocity of wave area high, model F (x) being fitted Function can be mainly reflected in weight λiChange, and desired value μiAnd standard deviation sigmaiThen vary less, keep the standard of fitting result True property.
4. practical simplicity, calculates rapid, it is easy to popularize.By the practical application that multiple work areas are carried out, as a result prove The present invention is technically feasible, is compared with additional fractionation method, and it calculates difference and is not more than 5%, and can more embody The actual conditions of work area rock mass.
Brief description of the drawings
Fig. 1 is the rock mass velocity Data-Statistics figure of actual measurement in the embodiment of the present invention；
Fig. 2 is normal distribution probability density curve fitting rock mass velocity probability density curve figure in the embodiment of the present invention；
Fig. 3 is normal distribution fitting 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) is that normal distribution is fitted rock mass classification.
Specific embodiment
Below in conjunction with the accompanying drawing in the present invention, the technical scheme 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 following step Suddenly：
Step one, 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, see Fig. 1.
The rock mass velocity Data-Statistics table of table 1
Velocity of wave (m/s) 2500 2530 2660 2730 2770 2810 2850 2890 2940 2980 3030 3070
Quantity (individual) 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 (individual) 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 (individual) 257 251 195 264 270 269 275 299 330 404 379 429
Velocity of wave (m/s) 5000 5120 5260 5400 5550 5710
Quantity (individual) 398 255 110 38 2 1
By the normalization of velocity of wave data probability：I.e. using formula is normalized, area between rock mass velocity value and abscissa line is 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 rock mass velocity value；
NiRepresent i-th number 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 is normalized；
Step 2, (determine normal distribution according to actual conditions using normpdf under least square method With 1 to 2 normpdf in the case of probability density function number, same work area, same lithology, complicated feelings More than 3 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 normpdf weight, λi>=0 and ∑ λi=1；
μiRepresent i-th normpdf expected value；
σiRepresent i-th normpdf Plays poor；
Velocity of wave data can should also be carried out with pre-treatment step before step 2 is performed, significantly isolated exceptional value is rejected Afterwards, then normpdf fitting is carried out.
Least square fitting rock mass velocity value probability density curve such as Fig. 2 is based on using normpdf Shown, in one of embodiment, rock mass velocity data model function is：
F (x)=0.46f (x, 3920,390)+(1-0.46) f (x, 4820,290)
Step 3, using normpdf f (x, μ, σ) curves at x=μ ± σ for flex point characteristic, With x=μ in rock mass velocity data model function F (x)i±σiAs rock mass classification standard value, using rock mass velocity data model letter Number F (x) expected value, standard deviation carry out rock mass classification.Classification basic principle is, when the suitable wall scroll normal distribution probability of velocity of wave is close When degree function curve is fitted, the first order is divided into more than μ+σ values with velocity of wave；With velocity of wave the is divided into more than μ-σ and less than μ+σ values Two grades；The third level is divided into less than μ-σ values with velocity of wave, as shown in Figure 3.When velocity of wave is adapted to two normpdfs During curve matching, averaged as cut off value at two curve adjacent comers, other are constant.
This method is classified sees Fig. 4 and table 2 with conventional method classification contrast.
The rock mass classification Comparison of standards table of table 2
The above, specific embodiment only of the invention, but protection scope of the present invention is not limited thereto, and it is any Belong to those skilled in the art the invention discloses technical scope in, the change or replacement that can be readily occurred in, all should It is included within the scope of the present invention.Therefore, protection scope of the present invention should be defined by scope of the claims.

Claims (4)

1. a kind of method that normal distribution fitting rock mass velocity divides rock-mass quality classification, it is characterised in that comprise the following steps：
Step one, 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 Normalized according to probability：
S = Σ i = 1 n - 1 ( N i + N i + 1 ) ( Vp i + 1 - Vp i ) / 2
D i = N i S
In above formula：N represents the quantity of different rock mass velocity values after sequencing statistical；
VpiRepresent i-th rock mass velocity value；
NiRepresent i-th number 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 is normalized；
Step 2, using normpdf under least square method
f ( x , μ , σ ) = 1 σ 2 π e ( - ( x - μ ) 2 2 σ 2 )
Velocity of wave data after Fitted probability normalization, obtain rock mass velocity data model function：
F ( x ) = Σ i = 1 n λ i · f ( x , μ i , σ i )
In above formula：N represents normpdf quantity；
λiRepresent i-th normpdf weight, λi>=0 and ∑ λi=1；
μiRepresent i-th normpdf expected value；
σiRepresent i-th normpdf Plays poor；
Step 3, using normpdf f (x, μ, σ) curves at x=μ ± σ for flex point characteristic, in rock mass With x=μ in velocity of wave data model function F (x)i±σiAs rock mass classification standard value, using rock mass velocity data model function F X () expected value, standard deviation carry out rock mass classification.
2. the method that normal distribution fitting rock mass velocity as claimed in claim 1 divides rock-mass quality classification, it is characterised in that： Basic principle is classified in step 3 is：It is big with velocity of wave when velocity of wave is adapted to wall scroll normpdf curve matching The first order is divided into μ+σ values；The second level is divided into more than μ-σ and less than μ+σ values with velocity of wave；It is worth less than μ-σ with velocity of wave and is divided It is the third level.
3. the method that normal distribution fitting rock mass velocity as claimed in claim 1 divides rock-mass quality classification, it is characterised in that： Also include that velocity of wave data should be carried out pre-treatment step before step 2, after rejecting significantly isolated exceptional value, then carry out normal state Distribution probability density function is fitted.
4. the method that normal distribution fitting rock mass velocity as claimed in claim 1 divides rock-mass quality classification, it is characterised in that： The normpdf quantity being fitted in step 2 determines regarding rock mass velocity statistic curve form medium wave peak number.
CN201710075731.6A 2017-02-13 2017-02-13 Normal distribution is fitted the method that rock mass velocity divides rock-mass quality classification Active CN106872579B (en)

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 true CN106872579A (en) 2017-06-20
CN106872579B 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)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110794039A (en) * 2019-11-06 2020-02-14 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
CN113050169A (en) * 2021-03-18 2021-06-29 长安大学 Rock mass anisotropy coefficient probability analysis method based on Monte Carlo sampling
CN113657515A (en) * 2021-08-20 2021-11-16 盾构及掘进技术国家重点实验室 Classification method for judging and improving tunnel surrounding rock grade of FMC model based on rock sensitivity parameters

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1480040A2 (en) * 2003-05-23 2004-11-24 Asociacion de Investigacion de las Industrias de la Construccion (AIDICO) Procedure to diagnose the quality in blocks of ornamental rock of large dimensions and devices for its implementation
CN106124632A (en) * 2016-07-22 2016-11-16 山东大学 A kind of concrete density appraisal procedure based on ultrasound wave
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

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1480040A2 (en) * 2003-05-23 2004-11-24 Asociacion de Investigacion de las Industrias de la Construccion (AIDICO) Procedure to diagnose the quality in blocks of ornamental rock of large dimensions and devices for its implementation
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
CN106124632A (en) * 2016-07-22 2016-11-16 山东大学 A kind of concrete density appraisal procedure based on ultrasound wave

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
唐升贵: "对岩体完整性指数计算中岩块波速的几点思考", 《土工基础》 *
胡世权: "声波测速在岩体完整性分类中的应用", 《山西建筑》 *

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110794039A (en) * 2019-11-06 2020-02-14 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
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
CN113050169A (en) * 2021-03-18 2021-06-29 长安大学 Rock mass anisotropy coefficient probability analysis method based on Monte Carlo sampling
CN113050169B (en) * 2021-03-18 2021-11-05 长安大学 Rock mass anisotropy coefficient probability analysis method based on Monte Carlo sampling
CN113657515A (en) * 2021-08-20 2021-11-16 盾构及掘进技术国家重点实验室 Classification method for judging and improving tunnel surrounding rock grade of FMC model based on rock sensitivity parameters

Also Published As

Publication number Publication date
CN106872579B (en) 2019-09-13

Similar Documents

Publication Publication Date Title
CN107590247B (en) Intelligent volume organizing method based on group knowledge diagnosis
Scheuring et al. Application of multifractals to the analysis of vegetation pattern
Spence et al. The determination of the underlying dimensionality of an empirically obtained matrix of proximities
CN107341497A (en) The unbalanced weighting data streams Ensemble classifier Forecasting Methodology of sampling is risen with reference to selectivity
CN106872579A (en) The method that normal distribution fitting rock mass velocity divides rock-mass quality classification
CN102298646A (en) Method and device for classifying subjective text and objective text
CN109241646B (en) Multi-factor two-dimensional soil-rock mixture generation method based on elliptical stacking and random field
CN106651147A (en) LCC-based power distribution network comprehensive benefit evaluation index comprehensive weight determination method
CN107169492A (en) Polarization SAR object detection method based on FCN CRF master-slave networks
CN103136247A (en) Attribute data interval partition method and attribute data interval partition device
CN105718943A (en) Character selection method based on particle swarm optimization algorithm
CN106228403A (en) A kind of user based on step analysis algorithm is worth methods of marking and system
CN110738232A (en) grid voltage out-of-limit cause diagnosis method based on data mining technology
CN104732003A (en) Grinding process assessment method based on reliability
CN109030014A (en) To the prediction technique of internal car noise subjective scoring when vehicle accelerates
CN106055871A (en) Evaluation method for gas recovery effect of gas well foam drainage
CN102073867A (en) Sorting method and device for remote sensing images
CN101226614A (en) Method for estimation of network assets essentiality
CN104318330B (en) The system and method for quick monte carlo method prediction ball mill grinding particle size distribution
CN109559017A (en) Technical index limit before foam drainage gas production implementation of gas well in Qinghai gas area and determination of technical index limit
Adami et al. The use of minimal spanning tree to characterize the 2d cluster galaxy distribution
CN115640995A (en) Tunnel advanced geological forecast risk evaluation method and device
Brown The fractal dimensions of lithic reduction
CN114580828A (en) Safety evaluation method for numerical control machine during transportation process
Kim et al. Multivariate analysis of CCSEM auto emission data

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