CN112067514B - Soil particle size detection method, system and medium based on geotechnical screening test - Google Patents
Soil particle size detection method, system and medium based on geotechnical screening test Download PDFInfo
- Publication number
- CN112067514B CN112067514B CN202010807294.4A CN202010807294A CN112067514B CN 112067514 B CN112067514 B CN 112067514B CN 202010807294 A CN202010807294 A CN 202010807294A CN 112067514 B CN112067514 B CN 112067514B
- Authority
- CN
- China
- Prior art keywords
- deviation
- interpolation
- coefficient
- particle diameter
- data point
- 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
- 239000002245 particle Substances 0.000 title claims abstract description 182
- 239000002689 soil Substances 0.000 title claims abstract description 62
- 238000012216 screening Methods 0.000 title claims abstract description 61
- 238000012360 testing method Methods 0.000 title claims abstract description 58
- 238000001514 detection method Methods 0.000 title claims abstract description 52
- 238000000034 method Methods 0.000 claims abstract description 138
- 238000004364 calculation method Methods 0.000 claims abstract description 64
- 239000011148 porous material Substances 0.000 claims description 44
- 230000006870 function Effects 0.000 claims description 21
- 238000004590 computer program Methods 0.000 claims description 15
- 230000004927 fusion Effects 0.000 claims description 12
- 238000003860 storage Methods 0.000 claims description 12
- 230000008569 process Effects 0.000 abstract description 11
- 238000010586 diagram Methods 0.000 description 15
- 238000004458 analytical method Methods 0.000 description 8
- 230000008859 change Effects 0.000 description 8
- 238000012545 processing Methods 0.000 description 7
- 238000013479 data entry Methods 0.000 description 4
- 238000012546 transfer Methods 0.000 description 3
- 230000009466 transformation Effects 0.000 description 3
- 238000009826 distribution Methods 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 102100035115 Testin Human genes 0.000 description 1
- 101710070533 Testin Proteins 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 239000008187 granular material Substances 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000035772 mutation Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/02—Investigating particle size or size distribution
- G01N15/0272—Investigating particle size or size distribution with screening; with classification by filtering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Chemical & Material Sciences (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Pure & Applied Mathematics (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- Mathematical Analysis (AREA)
- Computational Mathematics (AREA)
- Algebra (AREA)
- Dispersion Chemistry (AREA)
- Mathematical Optimization (AREA)
- Life Sciences & Earth Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a soil particle size detection method, a soil particle size detection system and a soil particle size detection medium based on a geotechnical screening test, which comprise the steps of inputting target particle size d and respectively using soil samples with aperture d 1 ～d n The mass percent m of the grain diameter obtained by screening detection of the screen mesh 1 ～m n The method comprises the steps of carrying out a first treatment on the surface of the Calculating a deviation coefficient of a specified interpolation method; obtaining the corresponding particle diameter mass percentage m j‑1 And m j+1 The mass percent of the grain diameter is m j‑1 And m j+1 Interpolation calculation is carried out by adopting a specified interpolation method to obtain the particle diameter mass percentage m of the target particle diameter d j The method comprises the steps of carrying out a first treatment on the surface of the Deviation coefficient of appointed interpolation method and mass percent m of particle diameter j And outputting. According to the invention, under the condition that the aperture of the screen is fixed and discontinuous in the geotechnical screening test process, the characteristic parameters such as the curvature coefficient, the non-uniformity coefficient and the like of the characteristic particle diameter d of a certain specific value m can be accurately measured, and the soil particle diameter detection precision of the geotechnical screening test can be effectively improved.
Description
Technical Field
The invention relates to a soil particle size detection technology, in particular to a soil particle size detection method, a soil particle size detection system and a soil particle size detection medium based on a geotechnical screening test.
Background
When the grading characteristics are evaluated by the geotechnical test, parameters such as curvature coefficient, non-uniformity coefficient and the like need to be calculated by knowing the characteristic particle diameter d (P < m) of which the mass percent P is smaller than a certain specific value m.However, during the test, the screen pore size was fixed and discontinuous, and direct determination of d (P < m) was not possible. In order to solve the above problems, the measurement d is generally used indirectly in the engineering i (P＜m i ) D i+1 (P＜m i+1 ) Method of "interpolation" wherein d i And d i+1 Respectively correspond to the standard sieve diameter, and reasonably select m i M i+1 Let m E (m) i ,m i+1 ) Inserting m linearly (m i ,d i (P＜m i ) (m) i+1 ,d i+1 (P＜m i+1 ) D (P < m) is obtained by calculating the distance between the points. The nature of "interpolation" is a calculation method that uses known data to infer unknown data in engineering practice. There are various interpolation modes, wherein linear interpolation is most widely applied, and the basic principle of calculation is to use triangle similarity relationship.
As shown in fig. 1, two points A, C are known to be two data points actually measured. Its coordinates are (x) A ,y A )、(x C ,y C ) A point between the B point location curves AC, its ordinate y B It is known that the abscissa x of the point B is now determined B . When linear interpolation is adopted, the curve AC is approximately replaced by the line segment AC, and the horizontal line is made to cross the line segment AC at the point B' by the point B. When the curve AC is more gentle or the AC point spacing is smaller, the engineering errors of the B point and the B 'point are acceptable, and then the coordinates of the B' point are approximately adopted to replace the coordinates of the B point. Since point B' is on line segment AC, when point B is known to be ordinate y B In the time, the abscissa x can be determined by geometric relationship B . Since RtΔADC and RtΔAEB' are similar, then there are:
because ae=x' B -x A ；AD＝x C -x A ；B′E＝y B -y A ；CD＝y C -y A ；
The substitution into formula (1) is as follows:
in formula (2), x is B’ As an unknown, solve for:
equation (3) is a calculation formula of linear interpolation.
In particular during particle analysis, if the particle size D is known to be < D 1 The mass percentage of soil particles is m 1 Particle diameter D < D 2 The mass percentage of soil particles is m 2 The mass percentage of the soil particles is m 0 When the particle size is smaller than D 'according to the formula (3)' 0 The method comprises the following steps:
the method is based on a linear coordinate system of m and d (P < m), but the screen diameter size is from 10 2 mm is changed to 10 -3 mm, the order of magnitude span is great, and under this coordinate system, adjacent known coordinate point interval distribution is extremely inhomogeneous, and the data presents nonlinear relation. The screening curve development in engineering has considered the problem, and the curve change trend is obviously reflected by adopting a semi-logarithmic coordinate, so that the estimated value of the characteristic particle diameter estimation is greatly deviated if linear interpolation is still adopted.
In a conventional rectangular coordinate system, the distance of a data point to the x or y axis is proportional to its coordinate value x or y, i.e., the coordinate system scale is uniform. However, this coordinate system has the disadvantage that when the value of x or y varies very much, the coordinate range spanned by the data points is very large, and if the value of x or y varies by a different order of magnitude, the curve becomes abnormally gentle or steep, making the curve features less obvious, and thus reducing the resolution of some features on the curve, as shown in fig. 2. However, if the original data is plotted by taking log of lg for the x and y data, respectively, and then replacing the original x and y data with lgx and lgy, the influence of the data index change on the image can be greatly reduced, as shown in fig. 3. As can be seen from comparing fig. 2 and 3, the same data, the curve drawn by using the linear coordinate system is very steep, the x-axis and y-axis ratios are very uneven, and the change trend of the data point is difficult to observe. However, if log of lg is taken for the x and y data respectively, the maximum value of lgx and lgy is not more than 1 order of magnitude, the whole curve is more symmetrical, and the change trend of the data is easier to observe.
The plotting of data points in a logarithmic coordinate system is divided into the following steps:
1. gathering raw data points (x, y);
2. taking log of the x, y data, new data points (lgx, lgy) are obtained;
3. drawing points in a coordinate system by taking lgx as an abscissa and lgy as an ordinate;
4. the points were connected by smooth curves.
As shown in fig. 4, in the logarithmic coordinate system, the measured coordinate length is not the real data x or y, and if it is assumed that the measured longitudinal and transverse axis lengths in the logarithmic coordinate system are X, Y, respectively, it can be seen from fig. 4:
the formula (5) is a formula for interconverting a logarithmic coordinate system and a linear coordinate system. The relation of X, Y variables in a logarithmic coordinate system can be conveniently converted into the relation of linear coordinate systems x and y by using the equation.
In practical engineering, the full-logarithmic coordinate system or the half-logarithmic coordinate system is flexibly selected according to the order of magnitude of the difference between the x and y data. The full logarithmic coordinate system is to take the logarithmic treatment of the variables x and y and then to spread the data points (lgx, lgy); the semi-logarithmic coordinate system is to take the logarithm of the variable x or y and then to spread the data points (lgx, y) or (x, lgy), and the images represented by the linear coordinate system, the semi-logarithmic coordinate system and the logarithmic coordinate system for the same set of data are shown in fig. 5.
As can be seen from a comparison of fig. 2 and 3, the linear correlation represented by the linear and logarithmic coordinate systems is different. Thus, a curve that shows nonlinearity in a linear coordinate system is not necessarily nonlinear in a logarithmic coordinate system, or the linear correlation in a logarithmic coordinate system is stronger, and this feature is more easily visually observed through the curve morphology. The interpolation calculation formula under the linear coordinate system given by the formula (3) and the formula (4) is essentially dependent on the curve form under the coordinate system and the geometrical similarity relationship, and has no relation with the selection of the type of the coordinate system. Thus, when the linear relationship of the curves characterized in the logarithmic coordinate system is more obvious when processing certain test data, we can try to calculate the unknown data by adopting the same linear interpolation method in the logarithmic coordinate system.
As shown in fig. 6, the data x is calculated by logarithm and then located on the logarithmic coordinate axis lgx. A. Three points B, C are three data points actually measured. Its coordinates are (lgx) A ,y A )、(lgx B ,y B )、(lgx C ,y C ). Under the coordinate system, A, C points are connected, the B point is used as a horizontal line, and the B point is intersected with the straight line AC to form a point B ', and the B' point is y=y B Corresponding log-linear interpolation points. According to the linear interpolation relationship, the substitution of x in equation (3) with lgx is followed by:
After the term transfer, the following steps are:
after the logarithmic transformation, the number of the logarithmic transformation is as follows:
thus, it can be solved that:
equation (9) is a calculation formula for linear interpolation according to semi-logarithmic coordinates, and varies according to an exponential rule, which is different from the linear interpolation method of equation (3). After knowing A (x A ,y A )、C(x C ,y C ) Point B ordinate y C The X-axis of the point B can be calculated through the method B’ 。
In particular during particle analysis, if the particle size D is known to be < D 1 The mass percentage of soil particles is m 1 Particle diameter D < D 2 The mass percentage of soil particles is m 2 The mass percentage of the soil particles is m 0 When the particle size is smaller than D 'according to the formula (3)' 0 The method comprises the following steps:
in summary, even though the screening curve in the engineering is drawn by considering the problems of extremely uneven distribution of the distance between adjacent known coordinate points and nonlinear relation of data, and the curve change trend is remarkably reflected by adopting semi-logarithmic coordinates, the estimated value of the screening curve in the engineering has larger deviation if linear interpolation is still adopted in the process of estimating the characteristic particle size.
Disclosure of Invention
The invention aims to solve the technical problems: aiming at the problems in the prior art, the invention provides a soil particle size detection method, a system and a medium based on a geotechnical screening test, which can accurately measure the characteristic parameters such as curvature coefficient, non-uniformity coefficient and the like of a characteristic particle size d (P < m) with mass percent P smaller than a certain specific value m under the condition that the aperture of a screen is fixed and discontinuous in the geotechnical screening test process, and can effectively improve the soil particle size detection precision of the geotechnical screening test.
In order to solve the technical problems, the invention adopts the following technical scheme:
the soil particle size detection method based on the geotechnical screening test comprises the following implementation steps:
1) Conveying deviceThe diameter d of the target particle diameter d and the pore diameter d of the soil sample are respectively used 1 ～d n The mass percent m of the grain diameter obtained by screening detection of the screen mesh 1 ～m n ；
2) For the mass percent m of the obtained particle size 1 ～m n Any intermediate data point m in (2) i According to the intermediate data point m i Two adjacent data points are calculated by adopting a specified interpolation method to obtain an interpolation data point m i Calculating an intermediate data point m i Interpolation data point m corresponding to the interpolation data point i Deviation Δm between i According to all the intermediate data points m i Deviation Δm of (a) i Calculating average relative deviation, sample standard deviation and variation coefficient, and calculating the deviation coefficient of the appointed interpolation method according to the average relative deviation, sample standard deviation and positive fusion of the variation coefficient; at a pore diameter d 1 ～d n Defining a maximum pore diameter d smaller than a target particle diameter d in the screen of (a) j-1 A minimum pore diameter d larger than the target particle diameter d j+1 Obtaining the corresponding particle diameter mass percentage m j-1 And m j+1 The mass percent of the grain diameter is m j-1 And m j+1 Interpolation calculation is carried out by adopting a specified interpolation method to obtain the particle diameter mass percentage m of the target particle diameter d j ；
3) Deviation coefficient of appointed interpolation method and mass percent m of particle diameter j And outputting.
Optionally, the calculation function expression of the deviation coefficient in step 2) is:
in the above formula, ψ is the deviation coefficient,
for average relative deviation, σ is sample standard deviation, c v Is the coefficient of variation.
Optionally, the expression of the function for calculating the variation coefficient is:
in the above, c v As the coefficient of variation, the number of the variations,
sigma is the sample standard deviation, which is the average relative deviation.
Optionally, the specified interpolation method is a linear interpolation method or a logarithmic interpolation method.
In addition, the invention also provides a soil particle size detection method based on a geotechnical screening test, which comprises the following implementation steps:
s1) inputting a target particle diameter d and using pore diameters d for soil samples 1 ～d n The mass percent m of the grain diameter obtained by screening detection of the screen mesh 1 ～m n ；
S2) for each of a plurality of interpolation methods preset, a current interpolation method: for the mass percent m of the obtained particle size 1 ～m n Any intermediate data point m in (2) i According to the intermediate data point m i Calculating two adjacent data points by adopting a current interpolation method to obtain an interpolation data point m i Calculating an intermediate data point m i Interpolation data point m corresponding to the interpolation data point i Deviation Δm between i According to all the intermediate data points m i Deviation Δm of (a) i Calculating average relative deviation, sample standard deviation and variation coefficient, and calculating the deviation coefficient of the current interpolation method according to the average relative deviation, sample standard deviation and positive fusion of the variation coefficient; selecting an interpolation method with the smallest deviation coefficient as an optimal interpolation method;
S3) at a pore diameter d 1 ～d n Defining a maximum pore diameter d smaller than a target particle diameter d in the screen of (a) j-1 A minimum pore diameter d larger than the target particle diameter d j+1 Obtaining the corresponding particle diameter mass percentage m j-1 And m j+1 The mass percent of the grain diameter is m j-1 And m j+1 Interpolation calculation is carried out by adopting an optimal interpolation method to obtain the particle diameter mass percentage m of the target particle diameter d j 。
Optionally, the preset plurality of interpolation methods include a linear interpolation method and a logarithmic interpolation method.
In addition, the invention also provides a soil particle size detection system based on a geotechnical screening test, which comprises the following components:
a data input program unit for inputting a target particle diameter d and a soil sample using pore diameters d, respectively 1 ～d n The mass percent m of the grain diameter obtained by screening detection of the screen mesh 1 ～m n ；
A deviation coefficient and result calculation program unit for calculating the mass percentage m of the obtained particle size 1 ～m n Any intermediate data point m in (2) i According to the intermediate data point m i Two adjacent data points are calculated by adopting a specified interpolation method to obtain an interpolation data point m i Calculating an intermediate data point m i Interpolation data point m corresponding to the interpolation data point i Deviation Δm between i According to all the intermediate data points m i Deviation Δm of (a) i Calculating average relative deviation, sample standard deviation and variation coefficient, and calculating the deviation coefficient of the appointed interpolation method according to the average relative deviation, sample standard deviation and positive fusion of the variation coefficient; at a pore diameter d 1 ～d n Defining a maximum pore diameter d smaller than a target particle diameter d in the screen of (a) j-1 A minimum pore diameter d larger than the target particle diameter d j+1 Obtaining the corresponding particle diameter mass percentage m j-1 And m j+1 The mass percent of the grain diameter is m j-1 And m j+1 Interpolation calculation is carried out by adopting a specified interpolation method to obtain the particle diameter mass percentage m of the target particle diameter d j ；
An output program unit for adding the deviation coefficient of the specified interpolation method and the mass percent of the particle size m j And outputting.
In addition, the invention also provides a soil particle size detection system based on a geotechnical screening test, which comprises the following components:
a data input program unit for inputting a target particle diameter d and a soil sample using pore diameters d, respectively 1 ～d n The mass percent m of the grain diameter obtained by screening detection of the screen mesh 1 ～m n ；
An interpolation method selection program unit for selecting, for each of a plurality of interpolation methods preset, a current interpolation method: for the mass percent m of the obtained particle size 1 ～m n Any intermediate data point m in (2) i According to the intermediate data point m i Calculating two adjacent data points by adopting a current interpolation method to obtain an interpolation data point m i Calculating an intermediate data point m i Interpolation data point m corresponding to the interpolation data point i Deviation Δm between i According to all the intermediate data points m i Deviation Δm of (a) i Calculating average relative deviation, sample standard deviation and variation coefficient, and calculating the deviation coefficient of the current interpolation method according to the average relative deviation, sample standard deviation and positive fusion of the variation coefficient; selecting an interpolation method with the smallest deviation coefficient as an optimal interpolation method;
A result calculation program unit for calculating the result of the calculation at the aperture d 1 ～d n Defining a maximum pore diameter d smaller than a target particle diameter d in the screen of (a) j-1 A minimum pore diameter d larger than the target particle diameter d j+1 Obtaining the corresponding particle diameter mass percentage m j-1 And m j+1 The mass percent of the grain diameter is m j-1 And m j+1 Interpolation calculation is carried out by adopting an optimal interpolation method to obtain the particle diameter mass percentage m of the target particle diameter d j 。
In addition, the invention also provides a soil particle size detection system based on the geotechnical screening test, which comprises a computer device, wherein the computer device is programmed or configured to execute the steps of the soil particle size detection method based on the geotechnical screening test, or a computer program programmed or configured to execute the soil particle size detection method based on the geotechnical screening test is stored in a memory of the computer device.
Furthermore, the invention also provides a computer readable storage medium, wherein the computer readable storage medium is stored with a computer program which is programmed or configured to execute the soil particle size detection method based on the geotechnical screening test.
Compared with the prior art, the invention has the following advantages:
1. according to the invention, under the condition that the aperture of the screen is fixed and discontinuous in the geotechnical screening test process, the characteristic parameters such as the curvature coefficient, the non-uniformity coefficient and the like of the characteristic particle diameter d of a certain specific value m can be accurately measured, and the soil particle diameter detection precision of the geotechnical screening test can be effectively improved.
2. The invention provides two interpolation calculation methods for comparison, and the optimal interpolation method can be rapidly and accurately obtained by utilizing the summarized deviation analysis method, so that the efficiency and accuracy of data processing in the geotechnical test process are effectively improved.
Drawings
Fig. 1 is a schematic diagram of the linear interpolation principle of the prior art.
Fig. 2 is a schematic diagram of a linear coordinate system of the prior art.
Fig. 3 is a log-coordinate system contrast diagram of the prior art.
Fig. 4 is a schematic diagram of a drawing principle of data points in a logarithmic coordinate system in the prior art.
Fig. 5 is a graph showing the comparison of the data representation of a linear coordinate system, a semilogarithmic coordinate system and a logarithmic coordinate system in the prior art.
Fig. 6 is a schematic diagram of the linear interpolation principle under the logarithmic coordinate system of the prior art.
FIG. 7 is a schematic diagram of a basic flow of a method according to an embodiment of the invention.
Fig. 8 is a schematic diagram of interpolation principle in an embodiment of the present invention.
FIG. 9 is a diagram illustrating the allocation of array variables during programming of a calculator according to an embodiment of the present invention.
FIG. 10 is a schematic diagram of a computer programming program according to an embodiment of the present invention.
Detailed Description
Embodiment one:
as shown in fig. 7, the soil particle size detection method based on the geotechnical screening test in this embodiment includes the following implementation steps:
1) The input target particle diameter d and the aperture d of the soil sample are respectively used 1 ～d n The mass percent of the grain diameter obtained by screening detection of the screen meshRatio m 1 ～m n ；
2) For the mass percent m of the obtained particle size 1 ～m n Any intermediate data point m in (2) i According to the intermediate data point m i Two adjacent data points are calculated by adopting a specified interpolation method to obtain an interpolation data point m i Calculating an intermediate data point m i Interpolation data point m corresponding to the interpolation data point i Deviation Δm between i According to all the intermediate data points m i Deviation Δm of (a) i Calculating average relative deviation, sample standard deviation and variation coefficient, and calculating the deviation coefficient of the appointed interpolation method according to the average relative deviation, sample standard deviation and positive fusion of the variation coefficient; at a pore diameter d 1 ～d n Defining a maximum pore diameter d smaller than a target particle diameter d in the screen of (a) j-1 A minimum pore diameter d larger than the target particle diameter d j+1 Obtaining the corresponding particle diameter mass percentage m j-1 And m j+1 The mass percent of the grain diameter is m j-1 And m j+1 Interpolation calculation is carried out by adopting a specified interpolation method to obtain the particle diameter mass percentage m of the target particle diameter d j ；
3) Deviation coefficient of appointed interpolation method and mass percent m of particle diameter j And outputting.
The method for predicting the data by adopting an interpolation mode needs to be given for measuring the deviation of the data so as to evaluate the interpolation precision, which is missing in most of the current data interpolation processes. In order to solve the above-described problem, the method of the present embodiment employs a deviation coefficient to evaluate interpolation accuracy of different interpolation modes to select an optimal interpolation mode. Aiming at the characteristic that the single test in the geotechnical screening test has less measured data, in the step 2) of the embodiment, the 'jump point method' checking interpolation precision is constructed by adopting the original data: as shown in fig. 8, assuming A, B, C, D, E as the actually measured data point, first, assuming that the B point is unknown, using the AC point to calculate the B 'point (region (1) in fig. 8) by linear interpolation of formula (3) or logarithmic interpolation of formula (6), and then comparing the B and B' point deviation values Δb; then, assuming that the point C is unknown, the point C 'is calculated (region No. (2) in fig. 8), and the point C' are compared with each other by the deviation Δc. And so on until all points have been traversed. In this way, all the dot position deviations except the first and last dot can be checked.
As can be seen from the above, the "jump point method" is adopted, and the relative deviation δ of each point can be calculated one by one according to the formula (11).
In the formula (11), delta i Representing the relative deviation of the ith point location, x i Representing the i-th true value, x' i The interpolation calculation result of the i-th value is represented. In the case where the interpolation accuracy is ideal, δ should tend to 0. Average relative deviation of sample ensemble
The smaller the sample standard deviation sigma is, the better the adaptability of the interpolation method to source data is represented, the more stable the performance is, and the average relative deviation is>
And the sample standard deviation sigma are calculated according to equations (12) and (13), respectively.
In the formulas (12) and (13), n is the number of points, delta i Representing the relative deviation of the ith point. Since the standard sieve diameter is changed from 150mm to 0.0075mm, the data change span is large, although the relative deviation delta is dimensionless, the interpolation accuracy is limited, and the situation that the relative deviation scale is changed greatly possibly exists is considered, the coefficient of variation is calculated by adopting the formula (14) to assist in evaluation.
Due to the average relative deviation of the whole geotechnical screening test
In the case of a better fit of the sample data estimate to the actual, the term->
It is likely to approach 0, so that +.about.>
A slight change is caused to cause a coefficient of variation c v And thus lose the meaning of guidance on the data.
Based on this, we hope that when
When the value goes to 0, c is in the formula (14) v On the premise of unchanged monotonicity, the value increasing rate is reduced, and the logarithmic processing is considered. In view of a minimum screen diameter of 10 -4 Order of magnitude, maximum screen diameter of 10 2 Order of magnitude, therefore, the logarithmic base takes 10 4 After transformation, c v At 10 -1 To 10 0 The number of the stages float, the change characteristics of the number of stages are easy to distinguish, and the expression of a calculation function defining the variation coefficient is as follows:
in the above, c v As the coefficient of variation, the number of the variations,
sigma is the sample standard deviation, which is the average relative deviation.
As can be seen from the foregoing, when evaluating the deviation of the interpolation method,
σ、c v the smaller the better. But is provided withWhen the mutation coefficient is calculated by the expression (15), there is a possibility that a negative number may occur, and the algebraic sum of the three may be simply taken, so that positive and negative cancellation may occur. Referring to the sample standard deviation definition method, in this embodiment, the expression of the function for calculating the deviation coefficient in step 2) is:
in the above formula, ψ is the deviation coefficient,
for average relative deviation, σ is sample standard deviation, c v Is the coefficient of variation. In actual engineering, for the same data point, using a 'jump point method', calculating the deviation coefficient of a sample by adopting linear interpolation and logarithmic linear interpolation respectively, and taking the interpolation parameter determined by the interpolation method with smaller deviation coefficient as an estimated value.
In the embodiment, 44 groups of geotechnical screening test data of large Gao Tiegai DIK184+000 to DIK187+150 segments of roadbed filling materials are taken as samples, and the measured particle size mass percentages smaller than 40mm, 20mm, 10mm, 5mm, 2mm, 1mm, 0.5mm, 0.25mm and 0.75mm are taken as true values, and the corresponding particle size d 'is reversely calculated by adopting a linear interpolation method and a logarithmic linear interpolation method respectively' 0 And with true particle diameter d 0 For comparison, the calculation process and the comparison result are shown in tables 1 to 4, respectively.
Table 1: linear interpolation calculation table.
In the above table, d 1 、m 1 、d 2 、m 2 Respectively refer to m 0 Adjacent characteristic particle size and mass percent; d, d 0 Is of actual particle size, d' 0 Particle size calculated for interpolation; delta is the absolute deviation of the estimated particle size, delta is the relative deviation of the estimated particle size, and the following table is the same. The parameters in the above table are calculated as follows:
table 2: a log linear interpolation calculation table.
The parameters in the above table are calculated as follows:
table 3: a table of deviation analysis of the linear interpolation data for each particle group.
Table 4: and each particle group is provided with a log linear interpolation data deviation analysis table.
As can be seen from the comparison of tables 3 and 4, for the same 44 sets of test data, the mean value of the relative deviation, the standard deviation of the relative deviation, and the deviation coefficient were all greater than those of the linear-to-logarithmic interpolation, except that the coefficient of variation of the linear interpolation was slightly greater than that of the linear-to-logarithmic interpolation. The deviation coefficient reflects the whole situation of interpolation deviation, so the logarithmic linear interpolation precision is superior to logarithmic interpolation.
Taking the data in Table 2 as an example, d is now calculated 60 、d 30 Curvature coefficient and non-uniformity coefficient.
From the data in the Table, 60. Epsilon. (54.2,69), d 54.2 ＝10，d 69 ＝20；30∈(25.5,33.6)，d 25.5 ＝1，d 33.6 =2; d is measured exactly in the test 10 =0.25; then it is known from formula (2):
so the non-uniformity coefficient C u ＝13.12/0.25＝52.5；C c ＝1.36 2 /(13.12×0.25)＝0.56。
Although the reliability of interpolation calculation is improved to a great extent by the method, the calculation process is complicated. For adapting to rapid and accurate calculation in engineering, a common calculation program is compiled by using a CASIO fx-5800P programmable function calculator so as to meet the requirements of on-site data recording and calculation. The difficulty with this programming is the storage and addressing of variables. As can be seen from the foregoing, the test data m i 、d i After input, they should be stored in the corresponding variables respectively first, and can be searched by index through natural number. For any given m 0 To calculate d by interpolation 0 First, m should be determined 0 At a known data point group m i This process is referred to as "addressing". After "addressing" is completed, m is needed 0 M of adjacent positions i 、d i And the result is transferred to other variables so as to facilitate subsequent interpolation operation. CASIO CASIO fx-5800P calculator having 26 alpha variables A-Z and Z1 in program editing mode]～Z[26]A total of 26 sets of variables. As shown in FIG. 9, m is stored for ease of recall and storage i 、d i Data, we use array variables Z [ i ]]To store test data entered during the input phase. Due to array variables Z [ i ]]There are 26 in total, and m is required to be stored separately i 、d i Two data, therefore we fold in half the total number of variables, Z1]～Z[13]For storing the characteristic particle diameter d i The method comprises the steps of carrying out a first treatment on the surface of the Will Z [14 ]]～Z[26]For storing the corresponding mass percentagesm i . Thus we build up a mass storage percentage m i And a corresponding characteristic particle diameter d i The same index is used for conveniently searching and calling the data input in the earlier stage during the later stage addressing. It follows that during the data entry phase, the maximum number of sets of grains that can be entered is 13 sets. Although the standard sieve has 14 particle groups for classification, in actual engineering, the situation of using 14 particle groups is quite small, so the variable group number can fully meet the engineering requirement.
According to the foregoing principle, considering practicality and usage habits, the program should have the following functions: 1. multiple result data (m i 、d i ) The method comprises the steps of carrying out a first treatment on the surface of the 2. When calculating by using the circularly input result data, a difference method (linear difference or logarithmic difference) can be selected; 3. the position of the parameter to be solved in the test array can be automatically searched; 4. and repeatedly calculating the parameter to be calculated by using the circularly input result data. The program structure constructed according to the above idea is shown in fig. 10, and is divided into five parts, namely "variable initialization", "variable assignment", "parameter addressing to be solved" and adjacent variable storage "," parameter to be solved by calculation according to different modes "and" calculation stop control switch ".
Before the program is run, the variables in the calculator should be initialized so as to avoid the influence of other data stored in the program. Notably, the built-in Clrmemory command does not clear the values stored in the array variable Z [ i ], so it is necessary to construct a loop to assign 0's to the array variable Z [ i ] one by one during the variable assignment process.
According to the analysis in the variable planning, the data input by the key can be continuously picked up and assigned to two types of array variables by constructing a loop, and attention is paid to the two types of array variables (m i 、d i ) Its index subscript constant phase difference 13.
After test data are entered and assigned to the corresponding variable group, for any given m 0 To calculate d by interpolation 0 It is necessary to find m 0 At a known data point group m i Is provided. By constructing a loop, within the loopSet m i ≤m 0 ≤m i+1 Is determined by the addressing conditions of (a) and m is determined by a traversing mode 0 And m is equal to i Respectively comparing once to determine m 0 Is a position of (c).
It should be noted here that: due to addressing conditions: m is m i ≤m 0 ≤m i+1 ，m i Is stored in order in array variable Z [ i ]]In, thus in (m) i 、d i ) The data is recorded in descending order when being recorded, otherwise, m is executed i ≤m 0 ≤m i+1 The program will make mistakes in the judgment. In engineering practice, the screened particle group data are also recorded in descending order, so that setting the data index in descending order has fully considered engineering operation habit, and thus the error probability is minimized.
m 0 After positioning, its adjacent (m i 、d i ) (m) i+1 、d i+1 ) Storing in alphabetical variables for later calling, transferring to compress program size, and directly calling Z [ i ]]When it needs to occupy 4 bytes, transfer Z [ i ] after transfer]Only 1 byte is required.
According to the content of the deviation analysis, the program should be compatible with two calculation modes of linear interpolation and logarithmic interpolation to provide comparison for error analysis and comparison. Setting a switch variable X, inputting a mode number by a user and assigning a value to the mode number, constructing a condition judgment, and respectively guiding a program to execute interpolation calculation under a corresponding mode according to different mode numbers as inlets.
After the test data is input, the user is considered to calculate any m 0 Corresponding d 0 May be more than once, e.g. d is calculated 15 D is also calculated 25 、d 30 And the like. In order to realize the function of one-time data input and multiple-time parameter calculation, the method needs to be carried out on m 0 Building a t condition loop before addressing, setting a switch variable Y, and calculating d once 0 And then, a user inputs a continuation code (1 or 0) according to a prompt and assigns the continuation code to a related variable Y to indicate whether the program finishes calculation or continues calculation of other parameters, so that the function of one-time data entry and multiple parameter calculation is realized.
When data is initialized and input, the data is input first and then the calculation mode is selected by taking the setting into consideration. Because test data entry is most time consuming, to avoid repeating the operations of entering data multiple times to improve efficiency, a calculation mode should be set to be performed after data entry. Otherwise, the data is re-recorded once when one computing mode is selected, so that the operation is few after the data is input, and the compatibility and the efficiency improvement of errors in engineering are not facilitated. Examples: when data is calculated, if a calculation mode is selected before data is input, after the data is input, the calculation mode is impossible to be changed, and after the calculation is finished according to the pre-selected calculation mode, the calculation mode is selected again and the data is input again, so that the method is practically infeasible in actual operation, and the program can give the operator enough opportunities to correct the early operation errors; if the calculation mode is adjusted to be carried out after the data input operation, the former data input only carries out assignment on the variables, and after the data input is completed, an operator can consider selecting the interpolation mode again, the data can be input once, the calculation values of different interpolation points of different interpolation modes can be calculated for a plurality of times, and the efficiency is far higher than that of the former. Finally, the following functions are realized through the program: 1. two calculation modes, linear interpolation and logarithmic linear interpolation, are provided. 2. At most 13 sets of granule set data are entered in a single support. 3. When the mass percentage is arbitrarily designated, the program can automatically search for adjacent mass percentages and corresponding characteristic particle sizes according to the input particle group data. 4. After only single test particle group data is input, the characteristic particle diameter of any mass percent can be repeatedly calculated, and the particle group data is not required to be repeatedly input. 5. Taking the habits of geotechnical screening tests and data recording into consideration, the data of the particle groups in the program are input in the sequence from large particle size to small particle size, and the data of the particle groups are uniquely corresponding to the calculation result. If the grain size recording order is opposite to the grain size recording order, calculation errors occur, and attention should be paid when the grain size recording method is used.
In addition, this embodiment still provides a soil particle diameter detecting system based on geotechnique screening test, includes:
a data input program unit for inputting the purposeStandard particle diameter d and pore diameter d for soil sample 1 ～d n The mass percent m of the grain diameter obtained by screening detection of the screen mesh 1 ～m n ；
A deviation coefficient and result calculation program unit for calculating the mass percentage m of the obtained particle size 1 ～m n Any intermediate data point m in (2) i According to the intermediate data point m i Two adjacent data points are calculated by adopting a specified interpolation method to obtain an interpolation data point m i Calculating an intermediate data point m i Interpolation data point m corresponding to the interpolation data point i Deviation Δm between i According to all the intermediate data points m i Deviation Δm of (a) i Calculating average relative deviation, sample standard deviation and variation coefficient, and calculating the deviation coefficient of the appointed interpolation method according to the average relative deviation, sample standard deviation and positive fusion of the variation coefficient; at a pore diameter d 1 ～d n Defining a maximum pore diameter d smaller than a target particle diameter d in the screen of (a) j-1 A minimum pore diameter d larger than the target particle diameter d j+1 Obtaining the corresponding particle diameter mass percentage m j-1 And m j+1 The mass percent of the grain diameter is m j-1 And m j+1 Interpolation calculation is carried out by adopting a specified interpolation method to obtain the particle diameter mass percentage m of the target particle diameter d j ；
An output program unit for adding the deviation coefficient of the specified interpolation method and the mass percent of the particle size m j And outputting.
In addition, the embodiment also provides a soil particle size detection system based on the geotechnical screening test, which comprises a computer device, wherein the computer device is programmed or configured to execute the steps of the soil particle size detection method based on the geotechnical screening test, or a computer program programmed or configured to execute the soil particle size detection method based on the geotechnical screening test is stored in a memory of the computer device.
In addition, the present embodiment also provides a computer readable storage medium having stored thereon a computer program programmed or configured to perform the aforementioned soil particle size detection method based on a geotechnical screening test.
Embodiment two:
in the first embodiment, the interpolation results and deviation coefficients of the interpolation methods are actually selected, and in addition, an optimal interpolation method can be automatically selected according to the deviation coefficients of the interpolation methods and the interpolation results can be output. In this embodiment, the method automatically selects an optimal interpolation method according to the deviation coefficient of the interpolation method and outputs the interpolation result.
The soil particle size detection method based on the geotechnical screening test in the embodiment comprises the following implementation steps:
s1) inputting a target particle diameter d and using pore diameters d for soil samples 1 ～d n The mass percent m of the grain diameter obtained by screening detection of the screen mesh 1 ～m n ；
S2) for each of a plurality of interpolation methods preset, a current interpolation method: for the mass percent m of the obtained particle size 1 ～m n Any intermediate data point m in (2) i According to the intermediate data point m i Calculating two adjacent data points by adopting a current interpolation method to obtain an interpolation data point m i Calculating an intermediate data point m i Interpolation data point m corresponding to the interpolation data point i Deviation Δm between i According to all the intermediate data points m i Deviation Δm of (a) i Calculating average relative deviation, sample standard deviation and variation coefficient, and calculating the deviation coefficient of the current interpolation method according to the average relative deviation, sample standard deviation and positive fusion of the variation coefficient; selecting an interpolation method with the smallest deviation coefficient as an optimal interpolation method;
s3) at a pore diameter d 1 ～d n Defining a maximum pore diameter d smaller than a target particle diameter d in the screen of (a) j-1 A minimum pore diameter d larger than the target particle diameter d j+1 Obtaining the corresponding particle diameter mass percentage m j-1 And m j+1 The mass percent of the grain diameter is m j-1 And m j+1 Interpolation calculation is carried out by adopting an optimal interpolation method to obtain the particle diameter mass percentage m of the target particle diameter d j 。
In this embodiment, the preset various interpolation methods include a linear interpolation method and a logarithmic interpolation method.
In addition, this embodiment still provides a soil particle diameter detecting system based on geotechnique screening test, includes:
a data input program unit for inputting a target particle diameter d and a soil sample using pore diameters d, respectively 1 ～d n The mass percent m of the grain diameter obtained by screening detection of the screen mesh 1 ～m n ；
An interpolation method selection program unit for selecting, for each of a plurality of interpolation methods preset, a current interpolation method: for the mass percent m of the obtained particle size 1 ～m n Any intermediate data point m in (2) i According to the intermediate data point m i Calculating two adjacent data points by adopting a current interpolation method to obtain an interpolation data point m i Calculating an intermediate data point m i Interpolation data point m corresponding to the interpolation data point i Deviation Δm between i According to all the intermediate data points m i Deviation Δm of (a) i Calculating average relative deviation, sample standard deviation and variation coefficient, and calculating the deviation coefficient of the current interpolation method according to the average relative deviation, sample standard deviation and positive fusion of the variation coefficient; selecting an interpolation method with the smallest deviation coefficient as an optimal interpolation method;
a result calculation program unit for calculating the result of the calculation at the aperture d 1 ～d n Defining a maximum pore diameter d smaller than a target particle diameter d in the screen of (a) j-1 A minimum pore diameter d larger than the target particle diameter d j+1 Obtaining the corresponding particle diameter mass percentage m j-1 And m j+1 The mass percent of the grain diameter is m j-1 And m j+1 Interpolation calculation is carried out by adopting an optimal interpolation method to obtain the particle diameter mass percentage m of the target particle diameter d j 。
In addition, the embodiment also provides a soil particle size detection system based on the geotechnical screening test, which comprises a computer device, wherein the computer device is programmed or configured to execute the steps of the soil particle size detection method based on the geotechnical screening test, or a computer program programmed or configured to execute the soil particle size detection method based on the geotechnical screening test is stored in a memory of the computer device.
In addition, the present embodiment also provides a computer readable storage medium having stored thereon a computer program programmed or configured to perform the aforementioned soil particle size detection method based on a geotechnical screening test.
Since the core method of the present embodiment is the same as that of the first embodiment, the technical effects of the core method are the same, and thus are not described herein.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above examples, and all technical solutions belonging to the concept of the present invention belong to the protection scope of the present invention. It should be noted that modifications and adaptations to the present invention may occur to one skilled in the art without departing from the principles of the present invention and are intended to be within the scope of the present invention.
Claims (8)
1. The soil particle size detection method based on the geotechnical screening test is characterized by comprising the following implementation steps:
1) The input target particle diameter d and the aperture d of the soil sample are respectively used 1 ～d n The mass percent m of the grain diameter obtained by screening detection of the screen mesh 1 ～m n ；
2) For the mass percent m of the obtained particle size 1 ～m n Any intermediate data point m in (2) i According to the intermediate data point m i Two adjacent data points are calculated by adopting a specified interpolation method to obtain an interpolation data point m i Calculating an intermediate data point m i Interpolation data point m corresponding to the interpolation data point i Deviation Δm between i According to all the intermediate data points m i Deviation Δm of (a) i Calculating average relative deviation, sample standard deviation and variation coefficient, and calculating the deviation coefficient of the appointed interpolation method according to the average relative deviation, sample standard deviation and positive fusion of the variation coefficient; at a pore diameter d 1 ～d n Defining a maximum pore diameter d smaller than a target particle diameter d in the screen of (a) j-1 A minimum pore diameter d larger than the target particle diameter d j+1 Obtaining the corresponding particle diameter mass percentage m j-1 And m j+1 The mass percent of the grain diameter is m j-1 And m j+1 Interpolation calculation is carried out by adopting a specified interpolation method to obtain the particle diameter mass percentage m of the target particle diameter d j ；
3) Deviation coefficient of appointed interpolation method and mass percent m of particle diameter j Outputting;
the expression of the calculation function of the deviation coefficient in the step 2) is as follows:
in the above formula, ψ is the deviation coefficient,
for average relative deviation, σ is sample standard deviation, c v Is a coefficient of variation, and has:
wherein n is the number of points, delta i Representing the relative deviation of the ith point location, x i Representing the i-th true value, x' i Representing the interpolation calculation result of the i-th value; the expression of the calculation function of the variation coefficient is as follows:
In the above, c v As the coefficient of variation, the number of the variations,
sigma is the sample standard deviation, which is the average relative deviation.
2. The soil particle size detection method based on a geotechnical screening test according to claim 1, wherein the specified interpolation method is a linear interpolation method or a logarithmic interpolation method.
3. The soil particle size detection method based on the geotechnical screening test is characterized by comprising the following implementation steps:
S1) inputting a target particle diameter d and using pore diameters d for soil samples 1 ～d n The mass percent m of the grain diameter obtained by screening detection of the screen mesh 1 ～m n ；
S2) for each of a plurality of interpolation methods preset, a current interpolation method: for the mass percent m of the obtained particle size 1 ～m n Any intermediate data point m in (2) i According to the intermediate data point m i Calculating two adjacent data points by adopting a current interpolation method to obtain an interpolation data point m i Calculating an intermediate data point m i Interpolation data point m corresponding to the interpolation data point i Deviation Δm between i According to all the intermediate data points m i Deviation Δm of (a) i Calculating average relative deviation, sample standard deviation and variation coefficient, and calculating the deviation coefficient of the current interpolation method according to the average relative deviation, sample standard deviation and positive fusion of the variation coefficient; selecting an interpolation method with the smallest deviation coefficient as an optimal interpolation method; wherein, the calculation function expression of the deviation coefficient is:
in the above formula, ψ is the deviation coefficient,
for average relative deviation, σ is sample standard deviation, c v Is a coefficient of variation, and has:
wherein n is the number of points, delta i Representing the relative deviation of the ith point location, x i Representing the i-th true value, x' i Representing the interpolation calculation result of the i-th value; the expression of the calculation function of the variation coefficient is as follows:
In the above, c v As the coefficient of variation, the number of the variations,
mean relative deviation, σ is sample standard deviation;
s3) at a pore diameter d 1 ～d n Defining a maximum pore diameter d smaller than a target particle diameter d in the screen of (a) j-1 A minimum pore diameter d larger than the target particle diameter d j+1 Obtaining the corresponding particle diameter mass percentage m j-1 And m j+1 The mass percent of the grain diameter is m j-1 And m j+1 Interpolation calculation is carried out by adopting an optimal interpolation method to obtain the particle diameter mass percentage m of the target particle diameter d j 。
4. A soil particle size detection method based on a geotechnical screening test according to claim 3, wherein the preset plurality of interpolation methods include a linear interpolation method and a logarithmic interpolation method.
5. Soil particle size detecting system based on geotechnical screening test, characterized by including:
a data input program unit for inputting a target particle diameter d and a soil sample using pore diameters d, respectively 1 ～d n The mass percent m of the grain diameter obtained by screening detection of the screen mesh 1 ～m n ；
Deviation coefficient and result calculation program elementFor the mass percentage m of the obtained particle diameter 1 ～m n Any intermediate data point m in (2) i According to the intermediate data point m i Two adjacent data points are calculated by adopting a specified interpolation method to obtain an interpolation data point m i Calculating an intermediate data point m i Interpolation data point m corresponding to the interpolation data point i Deviation Δm between i According to all the intermediate data points m i Deviation Δm of (a) i Calculating average relative deviation, sample standard deviation and variation coefficient, and calculating the deviation coefficient of the appointed interpolation method according to the average relative deviation, sample standard deviation and positive fusion of the variation coefficient; at a pore diameter d 1 ～d n Defining a maximum pore diameter d smaller than a target particle diameter d in the screen of (a) j-1 A minimum pore diameter d larger than the target particle diameter d j+1 Obtaining the corresponding particle diameter mass percentage m j-1 And m j+1 The mass percent of the grain diameter is m j-1 And m j+1 Interpolation calculation is carried out by adopting a specified interpolation method to obtain the particle diameter mass percentage m of the target particle diameter d j The method comprises the steps of carrying out a first treatment on the surface of the Wherein, the calculation function expression of the deviation coefficient is:
in the above formula, ψ is the deviation coefficient,
for average relative deviation, σ is sample standard deviation, c v Is a coefficient of variation, and has:
wherein n is the number of points, delta i Representing the relative deviation of the ith point location, x i Representing the i-th true value, x' i Representing the interpolation calculation result of the i-th value; the expression of the calculation function of the variation coefficient is as follows:
In the above, c v As the coefficient of variation, the number of the variations,
mean relative deviation, σ is sample standard deviation;
an output program unit for adding the deviation coefficient of the specified interpolation method and the mass percent of the particle size m j And outputting.
6. Soil particle size detecting system based on geotechnical screening test, characterized by including:
a data input program unit for inputting a target particle diameter d and a soil sample using pore diameters d, respectively 1 ～d n The mass percent m of the grain diameter obtained by screening detection of the screen mesh 1 ～m n ；
An interpolation method selection program unit for selecting, for each of a plurality of interpolation methods preset, a current interpolation method: for the mass percent m of the obtained particle size 1 ～m n Any intermediate data point m in (2) i According to the intermediate data point m i Calculating two adjacent data points by adopting a current interpolation method to obtain an interpolation data point m i Calculating an intermediate data point m i Interpolation data point m corresponding to the interpolation data point i Deviation Δm between i According to all the intermediate data points m i Deviation Δm of (a) i Calculating average relative deviation, sample standard deviation and variation coefficient, and calculating the deviation coefficient of the current interpolation method according to the average relative deviation, sample standard deviation and positive fusion of the variation coefficient; selecting an interpolation method with the smallest deviation coefficient as an optimal interpolation method; wherein, the calculation function expression of the deviation coefficient is:
in the above formula, ψ is the deviation coefficient,
for average relative deviation, σ is sample standard deviation, c v Is a coefficient of variation, and has:
wherein n is the number of points, delta i Representing the relative deviation of the ith point location, x i Representing the i-th true value, x' i Representing the interpolation calculation result of the i-th value; the expression of the calculation function of the variation coefficient is as follows:
In the above, c v As the coefficient of variation, the number of the variations,
mean relative deviation, σ is sample standard deviation;
a result calculation program unit for calculating the result of the calculation at the aperture d 1 ～d n Defining a maximum pore diameter d smaller than a target particle diameter d in the screen of (a) j-1 A minimum pore diameter d larger than the target particle diameter d j+1 Obtaining the corresponding particle diameter mass percentage m j-1 And m j+1 The mass percent of the grain diameter is m j-1 And m j+1 Interpolation calculation is carried out by adopting an optimal interpolation method to obtain the particle diameter mass percentage m of the target particle diameter d j 。
7. A soil particle size detection system based on a geotechnical screening test comprising a computer device, characterized in that the computer device is programmed or configured to perform the steps of the soil particle size detection method based on a geotechnical screening test according to any one of claims 1 to 4, or a computer program programmed or configured to perform the soil particle size detection method based on a geotechnical screening test according to any one of claims 1 to 4 is stored on a memory of the computer device.
8. A computer readable storage medium having stored thereon a computer program programmed or configured to perform the soil particle size detection method based on a geotechnical screening test of any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010807294.4A CN112067514B (en) | 2020-08-12 | 2020-08-12 | Soil particle size detection method, system and medium based on geotechnical screening test |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010807294.4A CN112067514B (en) | 2020-08-12 | 2020-08-12 | Soil particle size detection method, system and medium based on geotechnical screening test |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112067514A CN112067514A (en) | 2020-12-11 |
| CN112067514B true CN112067514B (en) | 2023-07-11 |
Family
ID=73662710
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010807294.4A Active CN112067514B (en) | 2020-08-12 | 2020-08-12 | Soil particle size detection method, system and medium based on geotechnical screening test |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112067514B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112816387B (en) * | 2020-12-31 | 2022-07-12 | 北京市水利规划设计研究院 | Method and device for determining permeability coefficient and storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH03195950A (en) * | 1989-12-25 | 1991-08-27 | Shimadzu Corp | Particle size distribution data processor |
| US5094532A (en) * | 1989-11-07 | 1992-03-10 | General Signal Corporation | Method and apparatus for measuring small particle size distribution |
| CN101430268A (en) * | 2008-12-18 | 2009-05-13 | 北京航空航天大学 | Integral inverse-calculation method for grain diameter measurement |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8423328B2 (en) * | 2009-09-30 | 2013-04-16 | International Business Machines Corporation | Method of distributing a random variable using statistically correct spatial interpolation continuously with spatially inhomogeneous statistical correlation versus distance, standard deviation, and mean |
-
2020
- 2020-08-12 CN CN202010807294.4A patent/CN112067514B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5094532A (en) * | 1989-11-07 | 1992-03-10 | General Signal Corporation | Method and apparatus for measuring small particle size distribution |
| JPH03195950A (en) * | 1989-12-25 | 1991-08-27 | Shimadzu Corp | Particle size distribution data processor |
| CN101430268A (en) * | 2008-12-18 | 2009-05-13 | 北京航空航天大学 | Integral inverse-calculation method for grain diameter measurement |
Non-Patent Citations (1)
| Title |
|---|
| 杜金龙 等.《焉耆盆地土壤颗粒分析试验及其研究意义》.《地质科技情报》.2008,第27卷(第4期),第90-94页. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112067514A (en) | 2020-12-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP6686056B2 (en) | Computer mounting method, computer system, and computer apparatus | |
| TWI584134B (en) | Method for analyzing variation causes of manufacturing process and system for analyzing variation causes of manufacturing process | |
| JP6951333B2 (en) | Wafer point-by-point analysis and data presentation | |
| CN112067514B (en) | Soil particle size detection method, system and medium based on geotechnical screening test | |
| CN114996280B (en) | Method, device, equipment and medium for correcting field information of data table | |
| CN114819636A (en) | Industrial production data processing method and system based on SPC detection | |
| US7412430B1 (en) | Determining the quality of computer software | |
| TW202013186A (en) | Data processing method, data processing device, data processing system, and computer-readable recording medium | |
| CN117029968A (en) | Traffic data diagnosis method, system, storage medium and electronic equipment | |
| CN102067064B (en) | Data processing device with adjustable performance level and method of operating such device | |
| CN113742248A (en) | Method and system for predicting organization process based on project measurement data | |
| TWI709833B (en) | Data processing method, data processing device, and computer-readable recording medium | |
| CN110399396B (en) | Efficient data processing | |
| CN111913945A (en) | Data management method and device and storage medium | |
| CN109686412B (en) | Data coordination processing method and device for metal balance | |
| JP2019003453A (en) | Defect factor analysis system and defect factor analysis method | |
| JP7135435B2 (en) | Information processing device and program | |
| EP1661038A1 (en) | A method of processing data for a system model | |
| CN110134265A (en) | Slide-mouse and its setup parameter adquisitiones | |
| CN116502568B (en) | Method, device, equipment and medium for automatically simulating internal flow characteristics of gas compressor | |
| CN116681340A (en) | Method for evaluating and improving differences among cigarette cut tobacco production batches | |
| TWI842961B (en) | Data processing method, data processing device and computer readable recording medium | |
| KR101340227B1 (en) | Method and computer-readable recording medium for treating helicopter flight test data | |
| Wampler | Analysis of the probability distribution of small random samples by nonlinear fitting of integrated probabilities | |
| CN117367583A (en) | Spectral curve band selection method, device, equipment and readable storage medium |
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 |