A TBM rock breaking efficiency evaluation method based on rock slag specific surface area

Abstract

This paper proposes a method for evaluating TBM rock-breaking efficiency based on the specific surface area of ​​rock ballast. The method comprises the following steps: collecting several groups of mixed-size rock ballast samples from different tunneling sections at the TBM construction site, conducting on-site rock ballast screening tests, and obtaining a cumulative distribution function for each group of rock ballast; conducting an indoor three-dimensional rock ballast scanning test to obtain a prediction function for the specific surface area of ​​the rock ballast; combining the cumulative distribution function with the specific surface area prediction function to calculate the specific surface area corresponding to each group of rock ballast samples; verifying the accuracy and rationality of the specific surface area calculation results using a new surface theory index; and calculating the specific energy and roughness index corresponding to each group of rock ballast based on on-site construction data and screening results. The relationship between the specific surface area of ​​the rock ballast and the specific energy and roughness index is analyzed to determine the TBM rock-breaking efficiency. This method can effectively describe the degree of rock ballast fragmentation and energy consumption, providing a new approach for predicting TBM tunneling performance.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel construction evaluation, and in particular to a TBM rock breaking efficiency evaluation method based on rock ballast specific surface area. Background Art

[0002] With the continuous development of manufacturing and construction technology, TBMs (Transport Bomb Machines) have been widely used in China due to their many advantages, including fast construction speed, low post-construction costs, and excellent safety. High-efficiency excavation, while ensuring construction safety, is the goal of TBM construction. Rock crushing requires energy. In rock crushing theory, three main theories explain the relationship between rock fragment size and energy dissipation after rock crushing: P.R. Rittinger's new surface theory, G. Kick's similarity theory, and F.C. Bond's crack theory. The new surface theory posits that rock crushing energy is primarily converted into the added surface energy of the rock fragment. In their paper "Theoretical and Experimental Study on the Crushing Work of Dangerous Coal," Cai Chenggong et al. compared and analyzed the degree of agreement between these three theories and coal rock crushing through indoor coal-rock drop hammer impact tests. The results showed that coal crushing conforms to the new surface theory, and that the energy consumed in crushing is proportional to the added surface area. To study the energy consumption characteristics of rockburst fragments, Su Guoshao et al. proposed a method for calculating total energy consumption based on the surface energy per unit area of ​​rockburst fragments in their paper "Experimental Study on Energy Consumption Characteristics of Rockburst Fragments at Different Loading Rates." Luo Jiayuan et al. conducted indoor crushing tests on raw coal in their paper "Experimental Study on the Relationship between Small Coal Particle Distribution and Crushing Work After Crushing," and found that the added surface area of ​​coal slag increases exponentially with energy.

[0003] Currently, few studies analyzing TBM excavation efficiency have used the surface area of ​​rock slag to evaluate and predict energy consumption under different excavation conditions from an energy conversion perspective. In "Evaluation Indicators for TBM Rock Breaking Efficiency Based on New Surface Theory," Yan Changbin et al. derived and defined new surface theory indicators based on the new surface theory, quantitatively predicting specific energy consumption and the optimal thrust range for TBMs. This provides new insights into TBM excavation performance analysis. However, this study did not include calculations of specific values ​​for rock slag surface area, instead using the theoretical proportional relationship between particle size and surface area as an equivalent substitute. Furthermore, due to the irregular shape of rock slag, existing studies typically simplify the rock slag into regular shapes such as spheres and ellipsoids when calculating its surface area, resulting in significant errors and low accuracy in surface area calculation models. Therefore, further research is needed to accurately calculate and use rock slag surface area to predict rock breaking efficiency.

[0004] The invention patent with application number 202110320352.5 discloses a method for evaluating the rock-breaking efficiency of TBMs based on the distribution law of rock slag particle size, which includes the following steps: measuring and screening the rock slag in a certain TBM excavation section at the TBM construction site, and calculating the total surface area of ​​the rock slag in the excavation section; calculating the effective rock-breaking ratio based on the total surface area of ​​the rock slag, and using the effective rock-breaking ratio to evaluate the rock-breaking efficiency of the TBM; the effective rock-breaking ratio is the percentage of the sum of the surface areas of rock slag with a particle size greater than 5mm to the sum of the surface areas of rock slag with full graded particle sizes. The effective rock-breaking ratio based on the total surface area of ​​rock slag proposed in the above invention eliminates the interference of the small-size rock slag content in the calculation of the total surface area index of rock slag, retains the advantage of the roughness index using the content of rock slag with larger particle sizes, and avoids the defects in the calculation of the roughness index, so it can better and more accurately describe the rock-breaking efficiency of the TBM. However, when the geological conditions are soft rock, the repeated crushing of rock slag and secondary wear of the tool make the relationship between TBM tool consumption and the content of rock slag of different shapes unclear, making it impossible to accurately evaluate the rock breaking efficiency. Summary of the Invention

[0005] In response to the technical problems existing in the existing TBM rock-breaking efficiency evaluation methods, the present invention proposes a TBM rock-breaking efficiency evaluation method based on the specific surface area of ​​rock slag. Using the specific surface area of ​​rock slag to evaluate TBM rock-breaking efficiency can provide a new approach for predicting TBM tunneling performance. The specific surface area of ​​rock slag is directly proportional to the specific energy and inversely proportional to the roughness index. It can better reflect the degree of rock slag crushing and more accurately evaluate the TBM rock-breaking efficiency.

[0006] To achieve the above-mentioned object, the technical solution of the present invention is implemented as follows: a TBM rock breaking efficiency evaluation method based on the specific surface area of ​​rock ballast, the steps of which are as follows:

[0007] Step 1: Take several groups of mixed-size rock slag samples from different excavation sections at the TBM construction site, conduct on-site rock slag screening tests, and obtain the cumulative distribution function f(x) of each group of rock slag;

[0008] Step 2: Conduct an indoor 3D scanning test of rock ballast to extract the particle size and specific surface area of ​​the rock ballast and obtain the specific surface area prediction function g(x);

[0009] Step 3: Using the integration principle, the cumulative distribution function f(x) and the specific surface area prediction function g(x) are combined to calculate the specific surface area value corresponding to each group of rock ballast samples;

[0010] Step 4: Verify the accuracy and rationality of the specific surface area calculation results through the new surface theoretical indicators;

[0011] Step 5: Calculate the specific energy and roughness index corresponding to each group of rock slag based on on-site construction data and screening results, analyze the relationship between the specific surface area of ​​rock slag and the specific energy and roughness index, and determine the TBM rock breaking efficiency.

[0012] Preferably, the method for obtaining the cumulative distribution function f(x) of each group of rock ballast is: fitting the screening results of the on-site screening test using the RR distribution function to obtain the cumulative distribution function f(x) of the rock ballast.

[0013] Preferably, the cumulative distribution function f(x) of rock ballast is f(x)=1-exp(-bx a );

[0014] Where x is the particle size of rock slag; f(x) is the mass fraction of rock slag with a particle size smaller than the rock slag particle size x; parameter a is the uniform distribution coefficient, and parameter b is the fitting coefficient.

[0015] Preferably, the three-dimensional scanning test is to randomly sample rock ballast of different particle size segments, obtain three-dimensional point cloud models of the rock ballast of different particle size segments using a three-dimensional scanner, and extract the particle size x, surface area SA and volume V of the rock ballast from the three-dimensional point cloud model using three-dimensional inverse software;

[0016] Through regression analysis, the rock slag particle size x and specific surface area S W1 The relationship function between the particle size and specific surface area of ​​rock ballast of different particle size segments is obtained by fitting, which is the specific surface area prediction function g(x).

[0017] Preferably, the density of rock ballast of the same lithology is the same, and the specific surface area S of rock ballast blocks of different particle size segments is calculated. W1 for:

[0018]

[0019] Where S W1 is the specific surface area of ​​the rock ballast; SA is the surface area of ​​the rock ballast; ρ is the density of the rock ballast; V is the volume of the rock ballast.

[0020] Preferably, the method for calculating the specific surface area of ​​each group of rock ballast samples is as follows: assuming that the total mass of a pile of mixed particle size rock ballast is a unit mass of 1g, the value of the cumulative distribution function f(x) is the cumulative mass of the rock ballast, and the specific surface area of ​​this pile of rock ballast is the particle size of 0~x max Total surface area of ​​rock ballast;

[0021] For 0~x max The surface area S of rock slag in all particle size intervals i By integrating and accumulating, we can get the total surface area of ​​the rock ballast, that is, the specific surface area:

[0022] Where S Wis the specific surface area of ​​the rock slag mixed sample, that is, the surface area per unit mass of rock slag, x max is the maximum rock slag particle size, f′(x) represents the difference of the rock slag cumulative distribution function f(x) in the particle size interval, S i For any particle size interval x i ~x i+1 The total surface area of ​​the internal rock ballast, and

[0023] Preferably, the specific surface area S of the ballast is W1 The specific surface area S of rock slag is the surface area per unit mass of rock slag after rock mass is crushed. W Indicates the size of the new surface area after the unit mass of rock is crushed; the new surface theoretical index S a It is proportional to the newly added surface area after the unit volume of rock is crushed. The specific surface area of ​​rock slag S W and the new surface theory index S a Both can measure the amount of new surface added during the rock crushing process, and the specific surface area of ​​rock slag S W and the new surface theory index S a The relationship between the specific surface area of ​​rock slag and the rock breaking efficiency of TBM is obtained by performing polynomial fitting on the specific surface area of ​​rock slag, roughness index and specific energy.

[0024] Preferably, the new surface theoretical index S a for:

[0025]

[0026] Where D is the particle size of rock slag before crushing, and d is the particle size after crushing;

[0027] According to the new surface theory, the particle size d of the crushed rock slag is calculated using the inverse weighted average method, namely:

[0028]

[0029] Where, γ i is the mass of the i-th group of rock ballast; d i represents the particle size of the i-th group of rock ballast;

[0030] The TBM excavation length per unit volume of rock is used instead of the rock particle size before crushing:

[0031]

[0032] Where R is the tunnel excavation radius.

[0033] Preferably, the cumulative screening rate of each sieve is obtained by the screening test, and the roughness index of the rock ballast is obtained by adding up the cumulative screening rates: CI = ∑X i,and

[0034] Where W i W is the total mass of rock slag larger than a certain particle size obtained from the on-site screening test; t is the total mass of TBM rock slag taken on site; X i It is the cumulative screening rate of particles larger than a certain particle size.

[0035] Preferably, the TBM excavation parameters corresponding to each group of rock ballast samples on that day are obtained by consulting the construction daily report or on-site monitoring records, and the average excavation thrust and specific energy are obtained. The specific energy is:

[0036] Where SE is specific energy; F v is the average thrust of the TBM during excavation; l is the excavation distance of the TBM in a certain period of time; M is the average torque of the TBM during excavation; θ is the angle of rotation of the cutter; R is the tunnel excavation radius.

[0037] Compared with the existing technology, the present invention has the following beneficial effects: the present invention can accurately calculate the true value of the specific surface area of ​​mixed-particle rock slag samples and verify the accuracy of its results. At the same time, it analyzes the relationship between the specific surface area of ​​rock slag and the specific energy and roughness index, and explores the feasibility of evaluating TBM rock-breaking efficiency based on specific surface area, which can provide new ideas for predicting TBM excavation performance. The present invention uses the specific surface area of ​​rock slag to evaluate TBM rock-breaking efficiency, which can better describe the degree of rock slag crushing and energy consumption. The larger the specific surface area, the more crushed the rock slag, the more energy consumed, and the lower the TBM rock-breaking efficiency, resulting in a more accurate evaluation effect. The present invention better reflects the degree of rock slag crushing and more accurately evaluates TBM rock-breaking efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0039] Figure 1 Flowchart of the present invention.

[0040] Figure 2 Schematic diagram of the cumulative distribution function f(x) of rock ballast in different tunneling sections obtained according to an embodiment of the present invention.

[0041] Figure 3 This is a three-dimensional model diagram of typical rock slag of different particle size segments obtained in an embodiment of the present invention.

[0042] Figure 4Schematic diagram of the specific surface area of ​​rock ballast obtained in an embodiment of the present invention.

[0043] Figure 5 The specific surface area S of the rock slag sample obtained in the embodiment of the present invention is W Relationship curve with the new surface theory index Sa.

[0044] Figure 6 The specific surface area S obtained in the embodiment of the present invention W Relationship curve with specific energy SE.

[0045] Figure 7 The specific surface area S obtained in one embodiment of the present invention is W Relationship curve with roughness index CI. DETAILED DESCRIPTION

[0046] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without creative work are within the scope of protection of the present invention.

[0047] Example 1

[0048] like Figure 1 As shown, a TBM rock breaking efficiency evaluation method based on the specific surface area of ​​rock ballast includes the following steps:

[0049] Step 1: Take several groups of mixed-size rock slag samples from different excavation sections at the conveyor outlet of the TBM construction site, conduct on-site rock slag screening tests, and obtain the cumulative distribution function f(x) of each group of rock slag.

[0050] The RR (Rosin-Rammler theory) distribution function is used to fit the screening results of the screening test to obtain the rock ballast cumulative distribution function f(x). The expression of the RR distribution function is:

[0051] f(x)=1-exp(-bx a )

[0052] Where x is the rock slag particle size, in mm; f(x) is the mass fraction of rock slag with a particle size smaller than the rock slag particle size x; parameter a is the uniform distribution coefficient. The smaller the value of parameter a, the wider the range of rock slag particle size distribution and the more uniform the particle size distribution. Where X = logx; In the x,y coordinate system, the curve of this equation is linear, and the slope is the value of parameter a. Parameter b is the fitting coefficient.

[0053] Step 2: Conduct an indoor three-dimensional scanning test of rock slag to accurately extract the information of the particle size and specific surface area of ​​the rock slag and obtain the specific surface area prediction function g(x) of the rock slag.

[0054] Random sampling of rock slag of different particle size segments is performed, and a three-dimensional point cloud model of the rock slag of different particle size segments is obtained using a three-dimensional scanner. Then, three-dimensional reverse software (such as Geomagic Studio) is used to accurately extract information such as the particle size (median axis) x, surface area SA, and volume V of the rock slag.

[0055] Furthermore, it can be assumed that the density of rock ballast of the same lithology is the same, and the specific surface area S of rock ballast blocks of different particle size segments can be calculated. W1 , the calculation formula is as follows:

[0056]

[0057] Where S W1 is the specific surface area of ​​rock ballast, cm 2 / g; SA is the surface area of ​​rock ballast, cm 2 ; ρ is the density of rock ballast g / cm 3 ; V is the volume of rock ballast, cm 3 .

[0058] Through regression analysis, the rock slag particle size x and specific surface area S W1 By fitting analysis, the relationship function between rock slag particle size and specific surface area, namely the specific surface area prediction function g(x), can be obtained.

[0059] Step three: Using the principle of integration, the cumulative distribution function f(x) and the specific surface area prediction function g(x) are combined to calculate the specific surface area value corresponding to each group of rock slag samples.

[0060] Calculate the specific surface area of ​​each group of rock slag samples: The specific surface area is defined as the total surface area per unit mass of rock slag (cm 2 / g), assuming that the total mass of a pile of mixed particle size rock slag is 1g, then the value of the cumulative distribution function f(x) is the cumulative mass of the rock slag, and the specific surface area of ​​the pile of rock slag is the particle size of 0~x max The total surface area of ​​the rock slag. Then, the mass △y of the rock slag in any particle size range x1~x2 is:

[0061] △y=f(x2)–f(x1)

[0062] In order to calculate the total surface area of ​​rock slag in the particle size range of x1 to x2, the particle size of this part of rock slag can be approximately equivalent to (x1+x2) / 2, then the total surface area of ​​rock slag in this particle size range S i for:

[0063]

[0064] Where S i is the total surface area of ​​rock slag in any particle size interval x1 to x2, cm 2 .

[0065] Taking this as an example, the particle size range can be divided into several parts, and the total surface area can be obtained by accumulating the sum after calculation. The smaller the interval is, the closer the cumulative calculation result is to the true value. Now differentiate the particle size range, and the length of each segment is dx. Then the mass △y of the rock slag in any particle size range x~x+dx is:

[0066] Δy=f′(x)dx;

[0067] The total surface area S of the rock slag in the particle size range of x to x + dx is i for:

[0068] S i =f′(x)dx×g(x);

[0069] For 0~x max The surface area S of rock slag in all particle size intervals i The total surface area of ​​the rock slag can be obtained by integrating and accumulating, that is, the specific surface area S W :

[0070]

[0071] Where S W is the specific surface area of ​​the rock slag mixed sample, that is, the surface area per unit mass of rock slag, cm 2 / g.x max is the maximum particle size of rock slag; f′(x) is the derivative of the rock slag cumulative distribution function at point x.

[0072] Step 4: Verify the accuracy and rationality of the specific surface area calculation results through new surface theoretical indicators.

[0073] Verification of the specific surface area of ​​rock slag sample: The specific surface area of ​​rock slag S W1 It indicates the surface area of ​​rock slag per unit mass after rock mass is crushed. Since the rock mass in the tunnel before TBM excavation is large and the exposed surface is small, the specific surface area of ​​the rock mass before crushing is much smaller than the specific surface area of ​​the rock slag after crushing and can be ignored. Therefore, the specific surface area of ​​the rock slag S is W It can approximately represent the size of the new surface area after the unit mass of rock is crushed. The new surface theoretical index S a It is proportional to the newly added surface area after the unit volume of rock is crushed, so the specific surface area of ​​rock slag S W and the new surface theory index S a Both can measure the amount of new surface area created during the rock crushing process, and the two should be in direct proportion.

[0074] If the particle size of rock slag before crushing is D and the particle size after crushing is d, the new surface theoretical index S a for:

[0075]

[0076] Where S a is the new surface theoretical index, mm -1 .

[0077] According to the new surface theory, the particle size d of the crushed rock fragments needs to be calculated using the inverse weighted average method, that is:

[0078]

[0079] Where, γ i is the mass of the ith group of rock ballast, kg. d i Represents the particle size of the i-th group of rock ballast.

[0080] The rock particle size D before crushing can be replaced by the TBM excavation length corresponding to the unit volume of rock, that is:

[0081]

[0082] Where R is the tunnel excavation radius, mm.

[0083] The specific surface area S corresponding to each group of rock slag samples W and the new surface theory index S a Linear regression analysis can be performed to verify the specific surface area S W Accuracy of results.

[0084] Step 5: Calculate the specific energy and roughness index corresponding to each group of rock slag based on on-site construction data and screening results, analyze the relationship between the specific surface area of ​​rock slag and the specific energy and roughness index, and determine the TBM rock breaking efficiency.

[0085] Fitting analysis of TBM rock-breaking efficiency indicators: A large number of existing studies have shown that roughness index and specific energy are commonly used indicators to reflect TBM rock-breaking efficiency. The larger the roughness index, the smaller the specific energy, and the higher the TBM rock-breaking efficiency.

[0086] The cumulative screening rate of each sieve is obtained from the screening test. The roughness index can be obtained by adding up the cumulative screening rates. The specific calculation formula is:

[0087]

[0088] CI=∑X i

[0089] Where W iis the total mass of rock slag larger than a certain particle size obtained from the on-site screening test, g; W t is the total mass of TBM rock slag taken on site, g; X i It is the cumulative screening rate of particles larger than a certain size, %; CI is the rock chip roughness index.

[0090] Furthermore, by consulting the daily construction report or on-site monitoring records, the TBM excavation parameters corresponding to each group of rock ballast samples on that day can be obtained, from which the average excavation thrust and specific energy can be obtained. The specific energy calculation formula is:

[0091]

[0092] Where SE is specific energy, kJ / m 3 ; F v is the average thrust of the TBM during excavation, kN; l is the excavation distance of the TBM in a certain period of time, m; M is the average torque of the TBM during excavation, kN·m; θ is the angle of rotation of the cutter, rad; R is the tunnel excavation radius, m.

[0093] Furthermore, the specific surface area of ​​rock slag was fitted with the roughness index and specific energy, and the relationship between the specific surface area of ​​rock slag and the TBM rock breaking efficiency was obtained using polynomial fitting.

[0094] Example 2

[0095] like Figure 1 As shown, a method for evaluating the rock breaking efficiency of a TBM based on the specific surface area of ​​rock ballast includes but is not limited to the following steps:

[0096] Step 1: Obtain the cumulative distribution function f(x) of rock slag: Eight groups of mixed-size rock slag samples from different excavation sections were collected at the conveyor outlet of the TBM construction site. Rock slag screening tests were conducted using standard square-hole sieves with apertures of 40 mm, 31.5 mm, 25 mm, 16 mm, 10 mm, 5 mm, and 2.5 mm (a total of seven levels). The screening results are shown in Table 1.

[0097] Table 1 Statistics of TBM rock slag screening test data in different tunneling sections

[0098]

[0099] By fitting the screening results in Table 1 with the RR theoretical distribution function, the cumulative distribution function f(x) of each group of rock slag samples can be obtained. Figure 2 The cumulative distribution function f(x) of rock ballast in different excavation sections is obtained by Figure 2 It can be seen that the particle size distribution functions of different lithologies have the same trend. 2 It can be seen that the degree of fitting is high.

[0100] Step 2: Obtain the prediction function g(x) for the specific surface area of ​​rock ballast: Randomly sample rock ballast of different particle size segments. Taking biotite granite as an example, a total of 168 rock ballasts were randomly selected from 8 particle size segments. The number of samples is shown in Table 2.

[0101] Table 2 Statistics of random sampling quantity of rock slag

[0102] Particle size range / mm >50 40～50 31.5～40 25～31.5 16～25 10～16 5～10 2.5～5 Number of samples 15 21 23 24 24 21 22 18

[0103] The 3D point cloud model of rock slag of different particle size segments is obtained through 3D scanning. Figure 3 The three-dimensional model of typical rock slag with different particle size segments is obtained by Figure 3 It can be seen that with the increase of particle size, the sphericity and flatness of the rock ballast gradually decrease, and the elongation gradually increases.

[0104] Geomagic Studio software is used to accurately extract the particle size (central axis) x, surface area SA, volume V and other information of the rock ballast, and the specific surface area S of the rock ballast blocks in different particle size segments is calculated. W1 The particle size and specific surface area are fitted and analyzed to obtain the prediction function g(x) of the specific surface area of ​​rock ballast. Figure 4 The figure shows the obtained prediction function g(x) of the specific surface area of ​​rock ballast. As the particle size of rock ballast increases, the specific surface area first decreases rapidly and then tends to be flat. The two show an obvious power function correlation relationship, and the correlation coefficient R 2 is 0.90.

[0105] Step three, calculate the specific surface area of ​​each group of rock slag samples: Under the premise that the functions f(x) and g(x) are known, the specific surface area integral formula can be solved by Matlab software, and the result is the specific surface area value of rock slag under different particle size distribution conditions. However, the function g(x) is not integrable at x=0. If the integral function is calculated starting from 0, the integral result will not converge. In fact, the particle size of rock powder produced by rock grinding is not infinitely close to 0. For example, Cai Zenghui conducted indoor grinding and screening tests on marble, sandstone and coal rock samples and found that the mass of rock powder with a particle size of less than 75μm is very small or even 0; Liu Xusan and others found that when studying the rock breaking mechanism of diamond drilling, the particle size of rock powder produced under grinding is usually above 2μm. Drawing on the results of previous studies, the minimum particle size of rock powder is taken as 0.002mm (2μm) and the maximum particle size of rock slag x max The maximum TBM cutter spacing can be selected, here 89 mm. The specific surface area values ​​calculated for each group of rock slag samples are shown in Table 3. Parameters related to rock breaking efficiency vary considerably among different lithologies, with granodiorite having a relatively small specific surface area.

[0106] Table 3 Specific surface area calculation results and TBM rock breaking efficiency related parameters

[0107]

[0108] Step 4: Verification of the specific surface area of ​​rock slag samples: Based on the screening results of 8 groups of rock slag samples, the new surface theoretical index S corresponding to each group of rock slag can be calculated. a .

[0109] Furthermore, the specific surface area S W and the new surface theory index S a Regression analysis was performed, and the results were as follows Figure 5 The specific surface area S of the rock slag sample obtained is shown as W and the new surface theory index S a relationship. Figure 5 It can be seen that the new surface theory index S a As the specific surface area S of rock ballast W The correlation coefficient R 2 is 0.987. Therefore, Figure 5 The results in the middle verify that the specific surface area of ​​rock ballast S W accuracy and rationality.

[0110] Step 5: The cumulative retention rate of each screen can be calculated from the screening results in Table 1. The roughness index can be obtained by adding up the cumulative retention rates. The specific energy can be calculated based on the on-site construction data. The specific results are shown in Table 3. Based on the data in Table 3, the specific surface area is fitted with the specific energy and the roughness index respectively.

[0111] like Figure 5 、 Figure 6 The relationship between the specific surface area of ​​rock ballast and specific energy and roughness index is shown in the figure. Figure 5 、 Figure 6 It can be seen that the specific surface area of ​​the rock slag sample is directly proportional to the specific energy and inversely proportional to the roughness index. This indicates that as the specific surface area of ​​the rock slag increases, the degree of rock slag fragmentation increases, the specific energy gradually increases, and the roughness index gradually decreases. Therefore, the specific surface area of ​​the rock slag can well reflect the rock breaking efficiency of the TBM. The larger the specific surface area, the more fragmented the rock slag and the lower the TBM rock breaking efficiency. Conversely, the smaller the specific surface area, the higher the TBM rock breaking efficiency.

[0112] Compared with the existing TBM rock breaking efficiency evaluation method, the specific surface area S W It has clearer physical meaning and more intuitive numerical results. Compared with the new surface theory index derived and defined based on the new surface theory to predict specific energy consumption and TBM optimal thrust range, the new surface theory index S a In the process of theoretical derivation, the theoretical proportional relationship between particle size and surface area, particle size and volume is used for substitution deduction, and the calculation of the specific value of the rock slag surface area is not involved. The specific surface area SW The result obtained is the true value of the specific surface area of ​​the rock ballast.

[0113] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for evaluating TBM rock breaking efficiency based on rock ballast specific surface area, characterized in that: The steps are as follows: Step 1: Take several groups of mixed-size rock slag samples from different excavation sections at the TBM construction site, conduct on-site rock slag screening tests, and obtain the cumulative distribution function f(x) of each group of rock slag; The cumulative distribution function f(x) is f(x)=1-exp(-bx a ); Where x is the particle size of rock slag; f(x) is the mass fraction of rock slag with a particle size smaller than the particle size x of rock slag; parameter a is the uniform distribution coefficient, and parameter b is the fitting coefficient; Step 2: Conduct an indoor 3D scanning test of rock ballast to extract the particle size and surface area of ​​the rock ballast and obtain the specific surface area prediction function g(x); The three-dimensional scanning test randomly samples rock ballast of different particle size segments, obtains three-dimensional point cloud models of the rock ballast of different particle size segments using a three-dimensional scanner, and extracts the particle size x, surface area SA and volume V of the rock ballast from the three-dimensional point cloud model using three-dimensional reverse software; Through regression analysis, the rock slag particle size x and specific surface area S W1 By fitting, the relationship function between the particle size and specific surface area of ​​rock ballast of different particle size segments is obtained as the specific surface area prediction function g(x); Step 3: Using the integration principle, the cumulative distribution function f(x) and the specific surface area prediction function g(x) are combined to calculate the specific surface area value corresponding to each group of rock ballast samples; Step 4: Verify the accuracy and rationality of the specific surface area calculation results through the new surface theoretical indicators; Step 5: Calculate the specific energy and roughness index corresponding to each group of rock slag based on on-site construction data and screening results, analyze the relationship between the specific surface area of ​​rock slag and the specific energy and roughness index, and determine the TBM rock breaking efficiency.

2. The TBM rock breaking efficiency evaluation method based on rock ballast specific surface area according to claim 1 is characterized in that: The method for obtaining the cumulative distribution function f(x) of each group of rock ballast is: fitting the screening results of the on-site screening test using the RR distribution function to obtain the cumulative distribution function f(x) of the rock ballast.

3. The TBM rock breaking efficiency evaluation method based on rock ballast specific surface area according to claim 1 is characterized in that: The density of rock slag of the same lithology is the same, and the specific surface area S of rock slag of different particle size segments is calculated. W1 for: Where S W1 is the specific surface area of ​​the rock ballast; SA is the surface area of ​​the rock ballast; ρ is the density of the rock ballast; V is the volume of the rock ballast.

4. The TBM rock breaking efficiency evaluation method based on rock ballast specific surface area according to claim 1 is characterized in that: The method for calculating the specific surface area of ​​each group of rock slag samples is as follows: assuming that the total mass of a pile of mixed particle size rock slag is a unit mass of 1g, the value of the cumulative distribution function f(x) is the cumulative mass of the rock slag, and the specific surface area of ​​this pile of rock slag is the particle size of 0~x max Total surface area of ​​rock ballast; For 0~x max The surface area S of rock slag in all particle size intervals i The total surface area of ​​the rock ballast is obtained by integration and accumulation, that is, the specific surface area: Where S W is the specific surface area of ​​the rock slag mixed sample, that is, the surface area per unit mass of rock slag, x max is the maximum rock slag particle size, f′(x) represents the difference of the rock slag cumulative distribution function f(x) in the particle size interval, S i For any particle size interval x i ~x i+1 The total surface area of ​​the internal rock ballast, and 5. The TBM rock breaking efficiency evaluation method based on rock ballast specific surface area according to claim 4 is characterized in that: Specific surface area S of rock ballast W Indicates the size of the new surface area after the unit mass of rock is crushed; the new surface theoretical index S a It is proportional to the newly added surface area after the unit volume of rock is crushed. The specific surface area of ​​rock slag S W and the new surface theory index S a Both can measure the amount of new surface added during the rock crushing process, and the specific surface area of ​​rock slag S W and the new surface theory index S a The relationship between the specific surface area of ​​rock slag and the rock breaking efficiency of TBM is obtained by performing polynomial fitting on the specific surface area of ​​rock slag, roughness index and specific energy.

6. The TBM rock breaking efficiency evaluation method based on rock ballast specific surface area according to claim 5 is characterized in that: The new surface theory index S a for: Where D is the particle size of rock slag before crushing, and d is the particle size after crushing; According to the new surface theory, the particle size d of the crushed rock slag is calculated using the inverse weighted average method, namely: Where, γ i is the mass of the i-th group of rock ballast; d i represents the particle size of the i-th group of rock ballast; The TBM excavation length per unit volume of rock is used instead of the rock particle size before crushing: Where R is the tunnel excavation radius.

7. The method for evaluating TBM rock breaking efficiency based on rock ballast specific surface area according to any one of claims 1 to 6, characterized in that: The cumulative screening rate of each screen is obtained from the screening test, and the roughness index of the rock ballast is obtained by adding up the cumulative screening rates: CI = ∑X i ,and Where W i W is the total mass of rock slag larger than a certain particle size obtained from the on-site screening test; t is the total mass of TBM rock slag taken on site; X i It is the cumulative screening rate of particles larger than a certain particle size.

8. The TBM rock breaking efficiency evaluation method based on rock ballast specific surface area according to claim 7 is characterized in that: By consulting the daily construction report or on-site monitoring records, the TBM excavation parameters corresponding to each group of rock ballast samples on that day were obtained, and the average excavation thrust and specific energy were obtained. The specific energy is: Where SE is specific energy; F v is the average thrust of the TBM during excavation; l is the excavation distance of the TBM in a certain period of time; M is the average torque of the TBM during excavation; θ is the angle of rotation of the cutter; R is the tunnel excavation radius.

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