Tunnel blasting explosive unit consumption optimization method and system

Abstract

The application discloses a tunnel blasting explosive unit consumption optimization method and system, electronic equipment and a computer readable storage medium, and belongs to the field of tunnel drilling and blasting technology. The method comprises the following steps: acquiring a tunnel blasting rock pile image, and generating a blasting fragment cumulative block degree curve; according to the blasting rock mass characteristics, the drilling geometry and the charging parameters, the average block degree of the blasting fragment is calculated through a blasting fragment block degree prediction model; according to the relationship between the image recognition average block degree of the blasting fragment cumulative block degree curve and the average block degree of the blasting fragment, and the maximum blasting block degree that can be loaded by the mechanical equipment, the allowable average block degree is calculated; and according to the allowable average block degree and the theoretical average block degree, the explosive unit consumption is calculated. The average block degree of blasting can be improved in a reasonable range, and the explosive unit consumption is effectively reduced; and the problems of high explosive unit consumption, serious waste and fine blasting fragment block degree in the prior art are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of tunnel drilling and blasting, in particular to a tunnel blasting explosive unit consumption optimization method and system. BACKGROUND

[0002] The statements in this section merely provide background information related to the present application and do not necessarily constitute the prior art.

[0003] Drilling and blasting is the most effective tunneling method for underground engineering, which is used to break the in-situ rock mass for economic and efficient loading, transportation and breaking of rock mass to the required size. At present, the explosive unit consumption of tunnel blasting excavation is generally much higher than that of mine blasting, and the explosive is seriously wasted. On the other hand, the blasting fragments produced by tunnel blasting are too fine, which causes dust flying, slow loading and transportation, threatens the occupational health of workers, and causes high cost and low productivity.

[0004] The factors affecting rock breaking are mainly divided into two categories: one is controllable factors, such as explosive unit consumption and explosive type; the other is uncontrollable factors, such as geological conditions. Scholars have developed various methods to evaluate the rock fragments produced by blasting, among which the most commonly used is the Kuz-Ram model. At present, the known blasting fragment distribution model is developed according to the data collected from open blasting, which is the blasting of large steps with two or three free surfaces, and its applicability in tunnel blasting is unknown.

[0005] However, the blasting operation in the tunnel has much more complex free surfaces than the step blasting, and the blasting effect also has great differences, which affects the accuracy of the evaluation of the blasting rock fragments. SUMMARY

[0006] In order to solve the problems of the prior art, the present application provides a tunnel blasting explosive unit consumption optimization method, system, electronic device and computer readable storage medium, which introduces image recognition technology, combines the theoretical average size of blasting fragments with the real picture recognition size, calculates the explosive unit consumption according to the maximum loading capacity of the loading equipment, thereby further controls the average size of blasting, reduces the content of fine particles of blasting, and improves the loading and transportation efficiency of blasting rock mass.

[0007] In a first aspect, the present application provides a tunnel blasting explosive unit consumption optimization method;

[0008] A tunnel blasting explosive unit consumption optimization method, comprising the following steps:

[0009] Obtaining a tunnel blasting rock pile image to generate a cumulative size curve of blasting fragments;

[0010] According to the blasting rock mass characteristics, the borehole geometry and the charge parameters, the average size of the blasting fragments is calculated through a blasting fragment size prediction model;

[0011] According to the relationship between the image recognition average size and the average size of the blasting fragments and the maximum blasting size that can be loaded by the mechanical equipment, the allowable average size is calculated;

[0012] According to the allowable average size and the theoretical average size, the explosive unit consumption is calculated.

[0013] In a second aspect, the present application provides a tunnel blasting explosive unit consumption optimization system;

[0014] A tunnel blasting explosive unit consumption optimization system comprises:

[0015] A blasting fragment cumulative size curve generation module is configured to acquire a tunnel blasting rock pile image and generate a blasting fragment cumulative size curve;

[0016] A blasting fragment average size calculation module is configured to calculate the average size of the blasting fragments according to the blasting rock mass characteristics, the borehole geometry and the charge parameters through a blasting fragment size prediction model;

[0017] An allowable average size calculation module is configured to calculate the allowable average size according to the relationship between the image recognition average size and the average size of the blasting fragments and the maximum blasting size that can be loaded by the mechanical equipment;

[0018] An explosive unit consumption calculation module is configured to calculate the explosive unit consumption according to the allowable average size and the average size of the blasting fragments.

[0019] In a third aspect, the present application provides an electronic device;

[0020] An electronic device comprises a memory and a processor, and computer instructions stored in the memory and running on the processor, when the computer instructions are run by the processor, the steps of the tunnel blasting explosive unit consumption optimization method described above are completed.

[0021] In a fourth aspect, the present application provides a computer readable storage medium;

[0022] A computer readable storage medium is used to store computer instructions, when the computer instructions are executed by a processor, the steps of the tunnel blasting explosive unit consumption optimization method described above are completed.

[0023] Compared with the prior art, the present application has the following beneficial effects:

[0024] The technical solution provided in this application introduces image recognition technology to analyze the actual fragment size distribution generated by blasting, links the actual average fragment size with the theoretically predicted average fragment size, establishes a regression model between the two, and then uses the maximum loading capacity of the loading equipment to calculate the allowable average fragment size. Finally, the unit consumption of explosives is reversed through the allowable average fragment size; the average fragment size of blasting is increased within the allowable range of mechanical equipment, effectively reducing the unit consumption of explosives, reducing the content of blasting fine particles, improving the loading and transportation efficiency of blasted rock mass, and reducing dust occupational hazards; it can expand the spacing between blasting holes according to the size of the loader, reduce the use of unit consumption of explosives, and reduce costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings in the specification, which constitute a part of this application, are used to provide further understanding of this application. The illustrative embodiments of this application and their descriptions are used to explain this application and do not constitute improper limitations on this application.

[0026] Figure 1 A schematic diagram of a process flow provided for an embodiment of the present application;

[0027] Figure 2 This is a schematic diagram of an example of a cumulative fragmentation curve of blasting fragments provided in an embodiment of the present application;

[0028] Figure 3 This is an example diagram of the regression equation provided in the embodiments of the present application. DETAILED DESCRIPTION

[0029] It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in this application have the same meaning as commonly understood by those skilled in the art to which this application belongs.

[0030] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] In the absence of conflict, the embodiments of the present invention and the features thereof may be combined with each other.

[0032] Example 1

[0033] In the prior art, in the tunnel drilling and blasting process, the unit consumption of explosives is seriously wasted, the blasting fragment size is too fine, and the environment and people are adversely affected, and the existing evaluation method cannot accurately predict the blasting fragment size; therefore, the application provides a tunnel blasting explosive unit consumption optimization method, which accurately predicts the blasting fragment size, and then inversely calculates the unit consumption of explosives, so as to improve the blasting fragment size within the range allowed by the mechanical equipment.

[0034] A tunnel blasting explosive unit consumption optimization method, comprising the following steps:

[0035] Obtaining a tunnel blasting rock pile image to generate a blasting fragment cumulative size curve;

[0036] According to the blasting rock mass characteristics, the borehole geometry and the charging parameters, the average size of the blasting fragments is calculated through a blasting fragment size prediction model;

[0037] According to the relationship between the average size of the blasting fragments and the maximum blasting size that can be loaded by the mechanical equipment, the allowable average size is calculated according to the image of the blasting fragment cumulative size curve;

[0038] According to the allowable average size and the theoretical average size, the unit consumption of explosives is calculated.

[0039] Further, the tunnel blasting rock pile is formed by more than 5 blasting footage.

[0040] Further, the tunnel blasting rock pile image is collected by a high-definition camera, and the shooting angle is perpendicular to the tunnel blasting rock pile.

[0041] Further, the blasting fragment size prediction model is as follows:

[0042]

[0043] Wherein, X 50 is the average size of the blasting fragments, A is the rock system number, q is the unit consumption of explosives, Q is the single-hole charge amount, and E is the relative weight blasting energy.

[0044] Further, the formula for calculating the unit consumption of explosives is as follows:

[0045]

[0046] Wherein, X 50 is the average size of the blasting fragments, A is the rock system number, q is the unit consumption of explosives, Q is the single-hole charge amount, and E is the relative weight blasting energy.

[0047] Further, the formula for calculating the allowable average size is as follows:

[0048] S 50 = S max -Dmax +D 50

[0049] wherein S max is the maximum rock block size that the transport channel of the reamer used in the tunneling can pass through, D 50 is the image recognition average block size, D max is the picture recognition maximum block size.

[0050] Further, regression analysis is performed on the average block size of the blasting fragments and the image recognition average block size, and a regression equation is established:

[0051] D 50 = 1.05 * X 50 + 1.34

[0052] wherein D 50 is the image recognition average block size, and X 50 is the average block size of the blasting fragments.

[0053] Next, in combination Figures 1-3 with the tunnel blasting explosive unit consumption optimization method disclosed in the embodiment, a detailed description is provided. Since the larger the average block size of the blasting is, the lower the required explosive unit consumption is, the technical solution provided in the embodiment analyzes the real fragment block size distribution generated by the blasting by introducing the image recognition technology; the real average block size is linked with the theoretically predicted average block size, and a regression model therebetween is established; then the maximum loading capacity of the loading equipment is used to calculate the allowable average block size; finally, the explosive unit consumption is back calculated through the allowable average block size. The embodiment provides a tunnel blasting explosive unit consumption optimization method, and the specific steps are as follows:

[0054] Step 1, acquiring a tunnel blasting rock pile image to generate a blasting fragment cumulative block size curve; wherein the tunnel blasting rock pile image is collected by a high-definition camera, and the shooting angle is perpendicular to the tunnel blasting rock pile; the blasting fragment cumulative block size curve is as shown in Figure 2 , the vertical coordinate is the cumulative content percentage, the horizontal coordinate is the fragment block size, presented in a logarithmic manner, the unit is cm, the image recognition average block size is D 50 , and the picture recognition maximum block size is D max ; the specific steps include:

[0055] Step 101, acquiring a tunnel blasting rock pile image to generate a rock mass blasting fragment boundary line; specifically, the boundary line of the rock mass blasting fragment in the tunnel blasting rock pile image can be recognized by an image recognition software to generate a rock mass blasting fragment boundary line;

[0056] Step 102, identifying the wrong boundary line and supplementing the missed boundary line according to the generated rock mass blasting fragment boundary line;

[0057] Step 103, highlight large rock blocks and fine particles in the rock blasting fragments;

[0058] Step 104, generate a cumulative block size curve of the blasting fragments according to the block size and frequency of the rock blasting fragments.

[0059] Step 2, calculate the average block size of the blasting fragments according to the characteristics of the blasting rock mass, the borehole geometry and the charging parameters, by using a blasting fragment block size prediction model; wherein the blasting fragment block size prediction model is as follows:

[0060]

[0061] wherein X 50 is the average block size of the blasting fragments, A is the rock mass coefficient, q is the specific charge of the explosive, Q is the single-hole charge, and E is the relative weight blasting energy;

[0062] For example, the ammonium nitrate fuel oil explosive E = 100, and the TNT explosive E = 115.

[0063] Step 3, as shown in Figure 3 , perform a linear regression analysis on the average block size of the blasting fragments and the image-identified average block size, and establish a regression equation:

[0064] D 50 = 1.05*X 50 + 1.34

[0065] wherein D 50 is the image-identified average block size, and X 50 is the average block size of the blasting fragments.

[0066] Step 4, calculate the allowable average block size according to the maximum blasting block size that can be loaded by the mechanical equipment, and the calculation formula of the allowable average block size is as follows:

[0067] S 50 = S max -D max + D 50

[0068] wherein S max is the maximum rock block size that can be passed by the transport channel of the tunnel mucking machine, D 50 is the image-identified average block size, and D max is the image-identified maximum block size.

[0069] Step 5, according to the allowable average block size, inverse the average block size of the blasting fragments; specifically, replace the image-identified average block size D 50 with the known allowable average block size S 50 , and according to the relationship model of D 50 and X 50 , inversely deduce the average block size X of the blasting fragments50 The size of the explosive.

[0070] Step 6, calculate the explosive unit consumption; the formula of calculating the explosive unit consumption is as follows:

[0071]

[0072] Wherein, X 50 The average size of the blasting fragments, A is the rock system number, q is the explosive unit consumption, Q is the single-hole charge, and E is the relative weight blasting energy.

[0073] Example two

[0074] The embodiment discloses a tunnel blasting explosive unit consumption optimization system, comprising:

[0075] The blasting fragment cumulative size curve generation module is configured to: acquire a tunnel blasting rock pile image, and generate a blasting fragment cumulative size curve;

[0076] The blasting fragment average size calculation module is configured to: according to the blasting rock mass characteristics, the borehole geometry and the charge parameters, calculate the average size of the blasting fragments through a blasting fragment size prediction model;

[0077] The allowable average size calculation module is configured to: according to the relationship between the image recognition average size of the blasting fragment cumulative size curve and the maximum blasting size that can be loaded by the mechanical equipment, calculate the allowable average size;

[0078] The explosive unit consumption calculation module is configured to: according to the allowable average size, inverse the average size of the blasting fragments, and calculate the explosive unit consumption.

[0079] It should be noted that the above-mentioned blasting fragment cumulative size curve generation module, blasting fragment average size calculation module, allowable average size calculation module and explosive unit consumption calculation module correspond to the steps in the first embodiment, and the above-mentioned modules and the examples and application scenarios realized by the corresponding steps are the same, but are not limited to the content disclosed in the above-mentioned first embodiment. It should be noted that the above-mentioned modules as part of the system can be executed in a computer system such as a group of computer executable instructions.

[0080] Example three

[0081] The embodiment three of the present application provides an electronic device, comprising a memory and a processor, and computer instructions stored in the memory and running on the processor, when the computer instructions are run by the processor, the steps are completed.

[0082] Example four

[0083] The fourth embodiment of the present application provides a computer readable storage medium for storing computer instructions, which, when executed by a processor, complete the steps described above.

[0084] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the computer or other programmable data processing devices generate a device that realizes the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus that realizes the functions specified in one or more flows and / or blocks.

[0085] These computer program instructions can also be stored in a computer readable memory that can direct the computer or other programmable data processing devices to work in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including instruction apparatus, which realizes the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus that realizes the functions specified in one or more flows and / or blocks.

[0086] These computer program instructions can also be loaded into a computer or other programmable data processing device to execute a series of operation steps to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide a process for realizing the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus that realizes the functions specified in one or more flows and / or blocks.

[0087] The description of each embodiment in the above embodiments is focused on each embodiment, and the parts not described in detail in a certain embodiment can refer to the related description of other embodiments.

[0088] The above only describes the preferred embodiments of the present application and is not used to limit the present application. For those skilled in the art, the present application can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method of optimizing the specific consumption of a tunnel blasting explosive, characterized in that, The method comprises the following steps: An image of a tunnel blasting rock pile is acquired, and a cumulative block size curve of the blasting fragments is generated; According to the characteristics of the blasting rock mass, the borehole geometry, and the charging parameters, the average block size of the blasting fragments is calculated through a blasting fragment block size prediction model; According to the relationship between the image-identified average block size of the cumulative block size curve and the average block size of the blasting fragments and the maximum blasting block size that can be loaded by the mechanical equipment, the allowable average block size is calculated; The calculation formula of the allowable average block size is as follows: where S max is the maximum rock block size that the transport channel of the reamer used for the tunnel can pass through, D 50 is the average block size identified from the image, D max is the maximum block size identified from the image; According to the allowable average block size, the average block size of the blasting fragments is inverted, and the explosive unit consumption is calculated; Regression analysis is performed on the average block size of the blasting fragments and the image-identified average block size, and a regression equation is established: D 50 = 1.05 * X 50 + 1.34 where D 50 is the average blockiness of the image recognition, X 50 is the average blockiness of the burst fragments.

2. The tunnelled blasting explosive unit consumption optimization method of claim 1, characterized by, The tunnel blasting rock pile is formed by more than five blasting footage.

3. The tunnelled blasting explosive unit consumption optimization method of claim 1, characterized by, The image of the tunnel blasting rock pile is collected by a high-definition camera, and the shooting angle is perpendicular to the tunnel blasting rock pile.

4. The tunnelled blasting explosive unit consumption optimization method of claim 1, characterized by, The blasting fragment block size prediction model is as follows: where X 50 is the average size of the blasted fragments, A is the rock system number, q is the specific charge of the explosive, Q is the charge per hole, and E is the relative weight of the blasting energy.

5. The tunnelled blasting explosive unit consumption optimization method of claim 4, characterized by, The formula for calculating the explosive unit consumption is as follows: where X 50 is the average size of the blasted fragments, A is the rock system number, q is the specific charge of the explosive, Q is the charge per hole, and E is the relative weight of the blasting energy.

6. A system for optimizing the specific charge of a tunnel blasting explosive, characterized by It comprises: The cumulative block size curve generation module is configured to acquire the image of the tunnel blasting rock pile and generate the cumulative block size curve of the blasting fragments; The average block size calculation module of the blasting fragments is configured to calculate the average block size of the blasting fragments through the blasting fragment block size prediction model according to the characteristics of the blasting rock mass, the borehole geometry, and the charging parameters; The allowable average block size calculation module is configured to calculate the allowable average block size according to the relationship between the image-identified average block size of the cumulative block size curve and the average block size of the blasting fragments and the maximum blasting block size that can be loaded by the mechanical equipment; the calculation formula of the allowable average block size is as follows: where S max is the maximum rock block size that the transport channel of the reamer used for the tunnel can pass through, D 50 is the average block size identified from the image, D max is the maximum block size identified from the image; The explosive unit consumption calculation module is configured to calculate the explosive unit consumption according to the allowable average block size by inverting the average block size of the blasting fragments; Regression analysis is performed on the average block size of the blasting fragments and the image-identified average block size, and a regression equation is established: D 50 = 1.05 * X 50 + 1.34 where D 50 is the average blockiness of the image recognition, X 50 is the average blockiness of the burst fragments.

7. An electronic device, comprising: It comprises a memory and a processor, and computer instructions stored on the memory and running on the processor, when the computer instructions are run by the processor, the steps of any one of claims 1-5 are completed.

8. A computer-readable storage medium, characterized in that, A computer instruction storage device, when the computer instruction is executed by the processor, the steps of any one of claims 1-5 are completed.

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