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
rock mass
wave velocity
normal distribution
probability density
velocity data
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

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00Investigating 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
    • G01N29/04Analysing solids
    • G01N29/07Analysing solids by measuring propagation velocity or propagation time of acoustic waves
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2291/00Indexing codes associated with group G01N29/00
    • G01N2291/02Indexing codes associated with the analysed material
    • G01N2291/023Solids
    • G01N2291/0232Glass, 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)
  • Investigation Of Foundation Soil And Reinforcement Of Foundation Soil By Compacting Or Drainage (AREA)
  • Investigating Or Analyzing Materials By The Use Of Ultrasonic Waves (AREA)

Abstract

本发明提供一种正态分布拟合岩体波速划分岩体质量分级的方法,包括如下步骤:步骤一、将实测的岩体波速数据按从小到大排序,并统计各波速数据的个数,将波速数据概率归一化;步骤二、利用最小二乘法下正态分布概率密度函数拟合概率归一化后的波速数据,得到岩体波速数据模型函数;步骤三、利用正态分布概率密度函数f(x,μ,σ)曲线在x=μ±σ处为拐点的特性,在岩体波速数据模型函数F(x)中以x=μi±σi作为岩体分级标准值,利用岩体波速数据模型函数F(x)中期望值、标准差进行岩体分级。本发明只根据工区岩体波速值,再利用统计学中正态分布概率密度函数来进行划分岩体质量分级划分,其可减少工地现场试验工作量,显著提高工效。

The present invention provides a method for grading rock mass quality by fitting rock mass wave velocities with normal distribution, comprising the following steps: step 1, sorting the measured rock mass wave velocities data from small to large, and counting the number of each wave velocity data, Normalize the wave velocity data probability; Step 2, use the normal distribution probability density function under the least squares method to fit the probability normalized wave velocity data, and obtain the rock mass wave velocity data model function; Step 3, use the normal distribution probability density The function f(x, μ, σ) curve is the inflection point at x=μ±σ. In the rock mass wave velocity data model function F(x), x=μ i ±σ i is used as the rock mass classification standard value, using The expected value and standard deviation in the rock mass wave velocity data model function F(x) are used to classify the rock mass. The invention only uses the normal distribution probability density function in statistics to classify the quality of the rock mass according to the wave velocity value of the rock mass in the work area, which can reduce the workload of field tests on the construction site and significantly improve the work efficiency.

Description

正态分布拟合岩体波速划分岩体质量分级的方法Method for Classifying Rock Mass Quality by Fitting Rock Mass Wave Velocity with Normal Distribution

技术领域technical field

本发明涉及工程勘察设计工程勘察设计技术领域,具体是一种正态分布拟合岩体波速划分岩体质量分级的方法。The invention relates to the technical field of engineering survey and design engineering survey and design, in particular to a method for dividing rock mass quality and grading by fitting rock mass wave velocity with normal distribution.

背景技术Background technique

目前在划分岩体质量分级方面,现有水利、电力、公路、铁路等各行业勘察领域均无具体明确的算法,目前各行业规程、规范均采用岩体坚硬程度(坚硬岩、较硬岩、较软岩、软岩、极软岩)与岩体完整程度(完整、较完整、较破碎、破碎、极破碎)列表对应方式来划分岩体质量分级。实际工作中,岩体质量分级划分一般根据实验室岩块测试结果(抗压强度,波速)、现场波速测试等数据再结合经验值来划分。存在的突出问题是计算方法不明确、掺杂个人经验、分级标准值不准确、工区实际情况针对性不强等缺陷。At present, in terms of classification of rock mass quality, there are no specific and clear algorithms in the existing water conservancy, electric power, highway, railway and other industry survey fields. Soft rock, soft rock, extremely soft rock) and rock mass integrity (complete, relatively complete, relatively broken, broken, extremely broken) are listed to classify rock mass quality. In actual work, the classification of rock mass quality is generally based on laboratory rock block test results (compressive strength, wave velocity), on-site wave velocity test data and other data combined with empirical values. The outstanding problems are that the calculation method is not clear, personal experience is mixed, the grading standard value is not accurate, and the actual situation of the work area is not targeted.

发明内容Contents of the invention

本发明的目的是提供一种更适用于工程勘察设计的较准确、更具针对性的岩体质量分级计算方法,即只根据工区岩体波速值,再利用统计学中正态分布概率密度函数来进行划分岩体质量分级划分。The purpose of the present invention is to provide a more accurate and more targeted rock mass quality classification calculation method that is more suitable for engineering survey and design, that is, only according to the wave velocity value of the rock mass in the work area, and then use the normal distribution probability density function in statistics To carry out the division of rock mass quality classification.

本发明的技术方案是这样实现的:Technical scheme of the present invention is realized like this:

一种正态分布拟合岩体波速划分岩体质量分级的方法,包括如下步骤:A method for dividing rock mass quality by fitting rock mass wave velocity with normal distribution, comprising the following steps:

步骤一、将实测的岩体波速数据按从小到大排序,并统计各波速数据的个数,将波速数据概率归一化:Step 1. Sort the measured rock mass wave velocity data from small to large, and count the number of each wave velocity data, and normalize the wave velocity data probability:

上式中:n代表排序统计后不同岩体波速值的数量;In the above formula: n represents the number of different rock mass wave velocity values after sorting statistics;

Vpi代表第i个岩体波速值;V pi represents the wave velocity value of the i-th rock mass;

Ni代表第i个岩体波速值的个数;N i represents the number of wave velocity values of the i-th rock mass;

S代表波速数据曲线与坐标横轴间面积;S represents the area between the wave velocity data curve and the horizontal axis of the coordinate;

Di代表概率归一化后波速数据的概率密度;D i represents the probability density of wave velocity data after probability normalization;

步骤二、利用最小二乘法下正态分布概率密度函数(根据实际情确定正态分布概率密度函数个数,同一工区,同一岩性的情况下用1至2个正态分布概率密度函数,复杂情况下可用3个以上正态分布概率密度函数)Step 2. Use the least squares method to determine the normal distribution probability density function (determine the number of normal distribution probability density functions according to the actual situation, use 1 to 2 normal distribution probability density functions in the same work area and the same lithology, which is complicated In some cases, more than 3 normal distribution probability density functions can be used)

拟合概率归一化后的波速数据,得到岩体波速数据模型函数:Fit the wave velocity data after probability normalization to obtain the rock mass wave velocity data model function:

上式中:n代表正态分布概率密度函数数量;In the above formula: n represents the number of normal distribution probability density functions;

λi代表第i个正态分布概率密度函数权重,λi≥0且∑λi=1;λ i represents the i-th normal distribution probability density function weight, λ i ≥ 0 and Σλ i = 1;

μi代表第i个正态分布概率密度函数中期望值;μ i represents the expected value in the i-th normal distribution probability density function;

σi代表第i个正态分布概率密度函数中标准差;σ i represents the standard deviation in the i-th normal distribution probability density function;

步骤三、利用正态分布概率密度函数f(x,μ,σ)曲线在x=μ±σ处为拐点的特性,在岩体波速数据模型函数F(x)中以x=μi±σi作为岩体分级标准值,利用岩体波速数据模型函数F(x)中期望值、标准差进行岩体分级。分级基本原则为,当波速适合单条正态分布概率密度函数曲线拟合时,以波速大于μ+σ值划分为第一级;以波速大于μ-σ且小于μ+σ值划分为第二级;以波速小于μ-σ值划分为第三级。当波速适合两条正态分布概率密度函数曲线拟合时,在两条曲线相邻拐点处取平均值作为分界值,其他不变。Step 3, using the characteristic of the normal distribution probability density function f(x, μ, σ) curve at x=μ±σ as the inflection point, in the rock mass wave velocity data model function F(x) with x=μ i ±σ i is used as the rock mass classification standard value, and the rock mass classification is carried out by using the expected value and standard deviation in the rock mass wave velocity data model function F(x). The basic principle of grading is that when the wave velocity is suitable for a single normal distribution probability density function curve fitting, the wave velocity greater than the value of μ+σ is divided into the first level; the wave velocity is greater than the value of μ-σ and less than the value of μ+σ into the second level ; It is divided into the third level by the wave velocity less than the μ-σ value. When the wave velocity fits two normal distribution probability density function curves, take the average value at the adjacent inflection points of the two curves as the cut-off value, and keep the others unchanged.

进一步的,步骤三中分级基本原则为:当波速适合单条正态分布概率密度函数曲线拟合时,以波速大于μ+σ值划分为第一级;以波速大于μ-σ且小于μ+σ值划分为第二级;以波速小于μ-σ值划分为第三级。Further, the basic principle of classification in step three is: when the wave speed is suitable for a single normal distribution probability density function curve fitting, the wave speed is greater than the value of μ+σ to be divided into the first level; the wave speed is greater than μ-σ and less than μ+σ The value is divided into the second level; the wave velocity is less than the μ-σ value is divided into the third level.

进一步的,步骤二之前还包括对波速数据应进行预处理步骤,剔除明显的孤立异常值后,再进行正态分布概率密度函数拟合。Further, before the second step, a preprocessing step should be performed on the wave velocity data, and after the obvious isolated outliers are eliminated, the normal distribution probability density function is then fitted.

进一步的,步骤二中进行拟合的正态分布概率密度函数数量视岩体波速统计曲线形态中波峰数确定。Further, the number of normal distribution probability density functions to be fitted in step 2 is determined depending on the number of peaks in the shape of the rock mass wave velocity statistics curve.

本发明的优点是:The advantages of the present invention are:

1.只需要岩体的波速值即可划分岩体分级,不需要其他岩体测试参数,从而减少工地现场试验工作量,可显著提高工效。1. Only the wave velocity value of the rock mass is needed to classify the rock mass, and no other rock mass test parameters are required, thereby reducing the workload of on-site testing and significantly improving work efficiency.

2.本方法建立在数理统计基础上,参与计算的岩体波速值越多,结果越能真实放映工区岩体实际情况。本发明可随着参与计算的岩体波速值的增多,及时修正。2. This method is based on mathematical statistics. The more rock mass wave velocity values involved in the calculation, the more realistic the results can reflect the actual situation of the rock mass in the work area. The present invention can be corrected in time with the increase of rock mass wave velocity values participating in the calculation.

3.引入权重λi可以降低模型函数中各正态分布概率密度函数中的期望值μi和标准差σi互相影响,如当波速测试数据大部分集中低波速区或高波速区时,所拟合的模型F(x)函数会主要体现在在权重λi的变化,而期望值μi和标准差σi则变化很小,保持拟合结果的准确性。3. Introducing the weight λ i can reduce the interaction between the expected value μ i and the standard deviation σ i in each normal distribution probability density function in the model function, such as when most of the wave velocity test data are concentrated in the low wave velocity area or high wave velocity area, the proposed The fitted model F(x) function will be mainly reflected in the change of weight λ i , while the expected value μ i and standard deviation σ i will change very little, maintaining the accuracy of the fitting result.

4.实用简便,计算迅速,易于推广普及。经过多个工区进行的实际应用,结果证明本发明在技术上是可行的,与传统分级方法相对比,其计算差异不大于5%,且更能体现出工区岩体的实际情况。4. Practical and simple, quick calculation, easy to popularize. After practical application in many work areas, the result proves that the present invention is technically feasible. Compared with the traditional grading method, the calculation difference is not more than 5%, and it can better reflect the actual situation of the rock mass in the work area.

附图说明Description of drawings

图1是本发明实施例中实测的岩体波速值统计图;Fig. 1 is the statistical diagram of the rock mass wave velocity value measured in the embodiment of the present invention;

图2是本发明实施例中正态分布概率密度曲线拟合岩体波速概率密度曲线图;Fig. 2 is a normal distribution probability density curve fitting rock mass wave velocity probability density curve figure in the embodiment of the present invention;

图3是本发明实施例中正态分布拟合岩体质量分级示意图;Fig. 3 is a schematic diagram of normal distribution fitting rock mass quality classification in the embodiment of the present invention;

图4是本发明正态分布拟合岩体分级与常规岩体分级对比图,其中图4(a)为常规岩体分级,图4(b)为正态分布拟合岩体分级。Fig. 4 is a comparison chart of normal distribution fitting rock mass classification and conventional rock mass classification of the present invention, wherein Fig. 4 (a) is conventional rock mass classification, and Fig. 4 (b) is normal distribution fitting rock mass classification.

具体实施方式detailed description

下面将结合本发明中的附图,对本发明中的技术方案进行清楚、完整地描述。The technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention.

本发明提供一种正态分布拟合岩体波速划分岩体质量分级的方法,包括如下步骤:The present invention provides a method for classifying rock mass quality by fitting rock mass wave velocity with normal distribution, comprising the following steps:

步骤一、将实测的岩体波速数据按从小到大排序,并统计各波速数据的个数,如表1所示,并绘制岩体波速值统计图,见图1。Step 1. Sort the measured rock mass wave velocity data from small to large, and count the number of each wave velocity data, as shown in Table 1, and draw a statistical map of rock mass wave velocity values, as shown in Figure 1.

表1岩体波速值统计表Table 1 Statistical table of wave velocity values of rock mass

波速(m/s)Wave speed (m/s) 25002500 25302530 26602660 27302730 27702770 28102810 28502850 28902890 29402940 29802980 30303030 30703070 数量(个)amount) 11 11 11 11 44 55 66 77 33 1313 1111 2727 波速(m/s)Wave speed (m/s) 31203120 31703170 32203220 32703270 33303330 33803380 34403440 35003500 35703570 36303630 37003700 37703770 数量(个)amount) 23twenty three 4343 3838 5555 8585 8686 123123 169169 188188 236236 223223 272272 波速(m/s)Wave speed (m/s) 38403840 39203920 40004000 40804080 41604160 42504250 43404340 44404440 45404540 46504650 47604760 48704870 数量(个)amount) 257257 251251 195195 264264 270270 269269 275275 299299 330330 404404 379379 429429 波速(m/s)Wave speed (m/s) 50005000 51205120 52605260 54005400 55505550 57105710 数量(个)amount) 398398 255255 110110 3838 22 11

将波速数据概率归一化:即利用归一化公式,将岩体波速值与坐标横轴间面积归为1,绘制岩体波速值概率密度曲线(岩体波速值概率密度曲线与岩体波速值统计曲线形态相似,为倍数关系)。Normalize the wave velocity data probability: that is, use the normalization formula to classify the area between the rock mass wave velocity value and the coordinate horizontal axis as 1, and draw the rock mass wave velocity value probability density curve (rock mass wave velocity value probability density curve and rock mass wave velocity The shape of the value statistics curve is similar, which is a multiple relationship).

上式中:n代表排序统计后不同岩体波速值的数量;In the above formula: n represents the number of different rock mass wave velocity values after sorting statistics;

Vpi代表第i个岩体波速值;Vpi represents the wave velocity value of the i-th rock mass;

Ni代表第i个岩体波速值的个数;N i represents the number of wave velocity values of the i-th rock mass;

S代表波速数据曲线与坐标横轴间面积;S represents the area between the wave velocity data curve and the horizontal axis of the coordinate;

Di代表概率归一化后波速数据的概率密度;D i represents the probability density of wave velocity data after probability normalization;

步骤二、利用最小二乘法下正态分布概率密度函数(根据实际情况确定正态分布概率密度函数个数,同一工区,同一岩性的情况下用1至2个正态分布概率密度函数,复杂情况下可用3个以上正态分布概率密度函数)Step 2. Use the least squares method to determine the normal distribution probability density function (determine the number of normal distribution probability density functions according to the actual situation, use 1 to 2 normal distribution probability density functions in the same work area and the same lithology, which is complicated In some cases, more than 3 normal distribution probability density functions can be used)

拟合概率归一化后的波速数据,得到岩体波速数据模型函数F(x)及各项参数(λi、μi、σi):Fit the wave velocity data after probability normalization to obtain the rock mass wave velocity data model function F(x) and various parameters (λ i , μ i , σ i ):

上式中:n代表正态分布概率密度函数数量;In the above formula: n represents the number of normal distribution probability density functions;

λi代表第i个正态分布概率密度函数权重,λi≥0且∑λi=1;λ i represents the i-th normal distribution probability density function weight, λ i ≥ 0 and Σλ i = 1;

μi代表第i个正态分布概率密度函数中期望值;μ i represents the expected value in the i-th normal distribution probability density function;

σi代表第i个正态分布概率密度函数中标准差;σ i represents the standard deviation in the i-th normal distribution probability density function;

在执行步骤二之前还可对波速数据应进行预处理步骤,剔除明显的孤立异常值后,再进行正态分布概率密度函数拟合。Before step 2, the wave velocity data should be preprocessed, and after removing obvious isolated outliers, the normal distribution probability density function can be fitted.

利用正态分布概率密度函数基于最小二乘法拟合岩体波速值概率密度曲线如图2所示,其中一个实施例中,岩体波速数据模型函数为:Utilize the normal distribution probability density function to fit the rock mass wave velocity value probability density curve based on the least squares method as shown in Figure 2, in one of the embodiments, the rock mass wave velocity data model function is:

F(x)=0.46·f(x,3920,390)+(1-0.46)·f(x,4820,290)F(x)=0.46 f(x,3920,390)+(1-0.46)f(x,4820,290)

步骤三、利用正态分布概率密度函数f(x,μ,σ)曲线在x=μ±σ处为拐点的特性,在岩体波速数据模型函数F(x)中以x=μi±σi作为岩体分级标准值,利用岩体波速数据模型函数F(x)中期望值、标准差进行岩体分级。分级基本原则为,当波速适合单条正态分布概率密度函数曲线拟合时,以波速大于μ+σ值划分为第一级;以波速大于μ-σ且小于μ+σ值划分为第二级;以波速小于μ-σ值划分为第三级,如图3所示。当波速适合两条正态分布概率密度函数曲线拟合时,在两条曲线相邻拐点处取平均值作为分界值,其他不变。Step 3, using the characteristic of the normal distribution probability density function f(x, μ, σ) curve at x=μ±σ as the inflection point, in the rock mass wave velocity data model function F(x) with x=μ i ±σ i is used as the rock mass classification standard value, and the rock mass classification is carried out by using the expected value and standard deviation in the rock mass wave velocity data model function F(x). The basic principle of grading is that when the wave velocity is suitable for a single normal distribution probability density function curve fitting, the wave velocity greater than the value of μ+σ is divided into the first level; the wave velocity is greater than the value of μ-σ and less than the value of μ+σ into the second level ; It is divided into the third level by the wave velocity less than the μ-σ value, as shown in Figure 3. When the wave velocity fits two normal distribution probability density function curves, take the average value at the adjacent inflection points of the two curves as the cut-off value, and keep the others unchanged.

本方法分级与常规方法分级对比见图4及表2。See Figure 4 and Table 2 for the comparison between the grading of this method and the grading of the conventional method.

表2岩体分级标准对比表Table 2 Comparison table of rock mass classification standards

以上所述,仅为本发明的具体实施方式,但本发明的保护范围并不局限于此,任何属于本技术领域的技术人员在本发明揭露的技术范围内,可轻易想到的变化或替换,都应涵盖在本发明的保护范围之内。因此,本发明的保护范围应该以权利要求的保护范围为准。The above is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto, any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention, All should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the protection scope of the claims.

Claims (4)

1.一种正态分布拟合岩体波速划分岩体质量分级的方法,其特征在于包括如下步骤:1. a method for normal distribution fitting rock mass wave velocity division rock mass quality classification is characterized in that comprising the steps: 步骤一、将实测的岩体波速数据按从小到大排序,并统计各波速数据的个数,将波速数据概率归一化:Step 1. Sort the measured rock mass wave velocity data from small to large, and count the number of each wave velocity data, and normalize the wave velocity data probability: SS == ΣΣ ii == 11 nno -- 11 (( NN ii ++ NN ii ++ 11 )) (( VpVp ii ++ 11 -- VpVp ii )) // 22 DD. ii == NN ii SS 上式中:n代表排序统计后不同岩体波速值的数量;In the above formula: n represents the number of different rock mass wave velocity values after sorting statistics; Vpi代表第i个岩体波速值;V pi represents the wave velocity value of the i-th rock mass; Ni代表第i个岩体波速值的个数;N i represents the number of wave velocity values of the i-th rock mass; S代表波速数据曲线与坐标横轴间面积;S represents the area between the wave velocity data curve and the horizontal axis of the coordinate; Di代表概率归一化后波速数据的概率密度;D i represents the probability density of wave velocity data after probability normalization; 步骤二、利用最小二乘法下正态分布概率密度函数Step 2. Use the probability density function of the normal distribution under the least squares method ff (( xx ,, μμ ,, σσ )) == 11 σσ 22 ππ ee (( -- (( xx -- μμ )) 22 22 σσ 22 )) 拟合概率归一化后的波速数据,得到岩体波速数据模型函数:Fit the wave velocity data after probability normalization to obtain the rock mass wave velocity data model function: Ff (( xx )) == ΣΣ ii == 11 nno λλ ii ·· ff (( xx ,, μμ ii ,, σσ ii )) 上式中:n代表正态分布概率密度函数数量;In the above formula: n represents the number of normal distribution probability density functions; λi代表第i个正态分布概率密度函数权重,λi≥0且∑λi=1;λ i represents the i-th normal distribution probability density function weight, λ i ≥ 0 and Σλ i = 1; μi代表第i个正态分布概率密度函数中期望值;μ i represents the expected value in the i-th normal distribution probability density function; σi代表第i个正态分布概率密度函数中标准差;σ i represents the standard deviation in the i-th normal distribution probability density function; 步骤三、利用正态分布概率密度函数f(x,μ,σ)曲线在x=μ±σ处为拐点的特性,在岩体波速数据模型函数F(x)中以x=μi±σi作为岩体分级标准值,利用岩体波速数据模型函数F(x)中期望值、标准差进行岩体分级。Step 3, using the characteristic of the normal distribution probability density function f(x, μ, σ) curve at x=μ±σ as the inflection point, in the rock mass wave velocity data model function F(x) with x=μ i ±σ i is used as the rock mass classification standard value, and the rock mass classification is carried out by using the expected value and standard deviation in the rock mass wave velocity data model function F(x). 2.如权利要求1所述的正态分布拟合岩体波速划分岩体质量分级的方法,其特征在于:步骤三中分级基本原则为:当波速适合单条正态分布概率密度函数曲线拟合时,以波速大于μ+σ值划分为第一级;以波速大于μ-σ且小于μ+σ值划分为第二级;以波速小于μ-σ值划分为第三级。2. the method for normal distribution fitting rock mass wave velocity division rock mass quality grading as claimed in claim 1, is characterized in that: in the step 3, classification basic principle is: when wave velocity fits single normal distribution probability density function curve fitting When the wave velocity is greater than the value of μ+σ, it is divided into the first level; if the wave speed is greater than μ-σ and less than the value of μ+σ, it is divided into the second level; if the wave speed is less than the value of μ-σ, it is divided into the third level. 3.如权利要求1所述的正态分布拟合岩体波速划分岩体质量分级的方法,其特征在于:步骤二之前还包括对波速数据应进行预处理步骤,剔除明显的孤立异常值后,再进行正态分布概率密度函数拟合。3. the method for normal distribution fitting rock mass wave velocity division rock mass quality classification as claimed in claim 1, it is characterized in that: before step 2, also comprise that wave velocity data should carry out preprocessing step, after removing obvious isolated outliers , and then fit the normal distribution probability density function. 4.如权利要求1所述的正态分布拟合岩体波速划分岩体质量分级的方法,其特征在于:步骤二中进行拟合的正态分布概率密度函数数量视岩体波速统计曲线形态中波峰数确定。4. the method for normal distribution fitting rock mass wave velocity division rock mass quality classification as claimed in claim 1, is characterized in that: the normal distribution probability density function quantity that carries out fitting in step 2 depends on rock mass wave velocity statistical curve form The number of peaks in the middle is determined.
CN201710075731.6A 2017-02-13 2017-02-13 Method for Classifying Rock Mass Quality by Fitting Rock Mass Wave Velocity with Normal Distribution Active CN106872579B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201710075731.6A CN106872579B (en) 2017-02-13 2017-02-13 Method for Classifying Rock Mass Quality by Fitting Rock Mass Wave Velocity with Normal Distribution

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201710075731.6A CN106872579B (en) 2017-02-13 2017-02-13 Method for Classifying Rock Mass Quality by Fitting Rock Mass Wave Velocity with Normal Distribution

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 Method for Classifying Rock Mass Quality by Fitting Rock Mass Wave Velocity with Normal Distribution

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
CN103093643B (en) Public parking lot berth quantity confirming method
CN103136247B (en) Attribute data interval division method and device
CN103886613B (en) A kind of rock structural face pattern anisotropy evaluation analysis method
CN106872579B (en) Method for Classifying Rock Mass Quality by Fitting Rock Mass Wave Velocity with Normal Distribution
CN103995947A (en) Improved coal seam floor water inrush vulnerability evaluation method
CN103995952A (en) An Improved Fuzzy Comprehensive Evaluation Method for Reclamation Suitability of Abandoned Mining Land
CN103839057A (en) Antimony floatation working condition recognition method and system
CN108106979A (en) A kind of PM2.5 inversion methods merged based on MODIS and machine learning model
CN104809311A (en) Structural part remaining life predicting method based on multi-factor fusion correction
CN110318808A (en) A kind of Rockburst Prediction Method introducing gradient stress
CN105550515A (en) Multi-level comprehensive judgment method for air quality data
CN106371080A (en) A radar target identification method based on geometrical structure characteristics and multi-feature combination
CN109030014A (en) To the prediction technique of internal car noise subjective scoring when vehicle accelerates
CN116542530A (en) A Landslide Susceptibility Assessment Method Introducing Dynamic Changes in Land Use
CN105824987A (en) Wind field characteristic statistical distributing model building method based on genetic algorithm
CN110705099A (en) Method for verifying output correlation of wind power plant
CN117330470A (en) Method for determining permeability tensor of three-dimensional fractured rock mass based on unidirectional permeability
CN109685334A (en) A kind of new hydrological model simulation evaluation method based on Multiscale Theory
Sandström et al. The field factor: towards a metric for academic institutions
CN104699961A (en) Method for calculating multiyear return period wave height of self-affine fractal on basis of Hurst rule
CN105607123B (en) Method and device for calculating seismic wave characteristic information of random pore medium model
CN102928871A (en) Rotation diamond based attribute extraction and fault description method
CN104569340B (en) Underground environment quality determination method and device
CN105512941A (en) Water landscape ecological project ecological service function test method and evaluation method
CN105825231A (en) Classification method for spectral features of space debris based on artificial intelligence

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