Hydraulic blasting risk assessment system based on big data

Abstract

The present invention discloses a water pressure blasting risk assessment system based on big data, comprising: an acquisition module, a processing module and an assessment module; wherein the acquisition module, the processing module, the assessment module and the prompt module are connected in sequence; the acquisition module is used to acquire geological data of a tunnel or tunnel engineering by a big data mining method; the processing module is used to construct a three-dimensional model according to the geological data, and simulate the three-dimensional model according to a water pressure blasting scheme, and acquire damage index values ​​according to the simulated model; the assessment module assesses the water pressure blasting risk according to the acquired damage index values, and obtains a water pressure blasting risk assessment result.

Description

Technical Field

[0001] The present invention belongs to the technical field of water pressure detection and evaluation, and in particular relates to a water pressure blasting risk evaluation system based on big data. Background Art

[0002] Hydraulic blasting is a special blasting method. It places explosive bags at the designed position in the water-filled container to be blasted, and uses water as the explosive medium to transmit the detonation pressure to destroy the container, while effectively controlling adverse factors such as air shock waves, flying rocks and noise. Hydraulic blasting uses the incompressible nature of water to effectively transfer the energy generated by the explosion of explosives to the container wall through water, forming a powerful shock wave, thereby achieving uniform disintegration and crushing of the container. In this process, the presence of water not only enhances the transmission efficiency of the explosion energy, but also has a good dust reduction and noise reduction effect. The new type of hydraulic blasting in tunnels refers to filling a certain amount of water bags at a certain position in the blasthole and using the water bags to backfill and block the blasthole mouth. At the moment of the explosion, the stress wave and expanding gas generated break the rock, which not only plays a role in dust reduction, but also increases the excavation footage, reduces the size of the slag blocks, reduces the unit consumption of explosives, and makes the slag pile relatively more concentrated, which is conducive to slag removal. It has the significant effect of "three increases and one improvement", that is, it improves the energy utilization rate of explosives, improves construction efficiency, improves economic benefits and improves the construction environment. It belongs to the "energy-saving and environmentally friendly" type of blasting. However, in the implementation of hydraulic blasting, it is necessary to conduct a risk assessment before blasting. Generally, it is assessed through the manual experience of relevant personnel. There is a lack of certain standards and it is impossible to conduct an effective risk assessment. Summary of the invention

[0003] In order to solve the above technical problems, the present invention proposes a water pressure blasting risk assessment system based on big data to solve the problems existing in the above prior art.

[0004] To achieve the above objectives, the present invention provides a water pressure blasting risk assessment system based on big data, comprising:

[0005] An acquisition module, a processing module and an evaluation module; wherein the acquisition module, the processing module and the evaluation module are connected in sequence;

[0006] The acquisition module is used to acquire geological data of a tunnel or tunnel engineering project by a big data mining method; the processing module is used to construct a three-dimensional model according to the geological data, simulate the three-dimensional model according to a hydraulic blasting scheme, and acquire damage index values ​​according to the simulated model; the evaluation module evaluates the hydraulic blasting risk according to the acquired damage index values ​​to obtain a hydraulic blasting risk evaluation result.

[0007] Optionally, in the processing module, a three-dimensional model is constructed according to the geological data using finite element analysis software, the three-dimensional model including a geological model and a hydraulic blasting model, the hydraulic blasting model in the three-dimensional model is set according to the hydraulic blasting plan, and the three-dimensional model is simulated using a numerical simulation method of hydraulic blasting.

[0008] Optionally, in the processing module, the damage index value includes a horizontal damage index value and a vertical damage index value.

[0009] Optionally, in the processing module, the process of obtaining the horizontal damage index value includes:

[0010] The overall damage range is divided into horizontal intervals to obtain different horizontal intervals; the overall damage range is the area after the test range area in the model after simulation is removed from the first range area, wherein the first range area is the ideal blasting range of the hydraulic blasting scheme in the three-dimensional model, and the test range area is a rectangular area that is expanded outward to a fixed ratio with the same center and in different directions of the first range area, and the entire expanded area is covered by the smallest rectangular area;

[0011] The damage range of the horizontal interval is counted to obtain a horizontal damage range value, and a normal distribution weight is assigned to the horizontal interval. According to the weight assignment result, the horizontal damage range value is weighted and calculated to obtain a horizontal damage index value.

[0012] Optionally, in the processing module, the process of obtaining the horizontal damage index value includes:

[0013] The overall damage range is divided into vertical intervals to obtain different vertical intervals, the damage ranges of the vertical intervals are counted to obtain vertical damage range values, weights of the vertical intervals are initially allocated, threshold judgment is performed on the damage range values ​​of the vertical intervals, and the initially allocated weights are adjusted according to the threshold judgment result. Based on the adjusted weights, the vertical damage range values ​​are weighted and calculated to obtain a vertical damage index value.

[0014] Optionally, adjusting the initially assigned weight includes: when there is a vertical interval with a damage range greater than a threshold in a continuous vertical interval, increasing the weight of the vertical interval, wherein the weight of the continuous vertical interval is adjusted to the number of consecutive intervals greater than the threshold × a fixed value + the initial vertical weight.

[0015] Optionally, in the evaluation module, the risk of hydraulic blasting is evaluated according to the acquired damage index values ​​by using a fuzzy evaluation method.

[0016] Compared with the prior art, the present invention has the following advantages and technical effects:

[0017] Through the above-mentioned technical scheme, the present invention uses a hydraulic blasting risk assessment system to effectively determine the geological data of a tunnel or tunnel engineering project by means of big data mining, and constructs a three-dimensional model based on the determined geological data. After the construction, the hydraulic blasting is simulated and simulated, and the risk of the hydraulic blasting is assessed through the simulation and the simulated model. In the present invention, different interval damage scores are set through an adaptive weight setting method, and an effective risk assessment of the damage index is performed through a simulation evaluation method. At the same time, the risk assessment provides a relevant theoretical basis for subsequent actual operations, and has strong practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0019] Figure 1 Schematic diagram of a system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0020] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0021] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0022] like Figure 1 As shown, this embodiment provides a water pressure blasting risk assessment system based on big data, including:

[0023] An acquisition module, a processing module and an evaluation module; wherein the acquisition module, the processing module and the evaluation module are connected in sequence;

[0024] The acquisition module is used to obtain relevant geological data through big data retrieval and mining. The processing module constructs a three-dimensional simulation model through the geological data, sets the mode and position of the water pressure blasting in the three-dimensional simulation model, and after the setting is completed, generates a model after blasting through the three-dimensional simulation model and the water pressure blasting process corresponding to the simulation model. The model after blasting is divided into regions and the damage index value is obtained after the regional division. The evaluation module evaluates the risk of water pressure blasting according to the damage index value.

[0025] The present invention mainly evaluates the simulation results produced by the water pressure blasting method used in tunnel blasting excavation of tunnel or tunnel engineering, so as to predict and evaluate the influence of water pressure blasting on the tunnel blasting excavation of tunnel or tunnel engineering.

[0026] The acquisition module obtains geological data by means of big data mining. The geological data mainly includes relevant geological data for building relevant three-dimensional models for the needs of relevant areas of tunnels or tunnel projects. Specifically, geological data has the characteristics of various types, large data volume, and strong spatiality. Data types include text, images, spatial data, etc. These relevant geological data of tunnels or tunnel projects are often stored in a variety of different formats and systems. In addition, geological data also has a strong spatial attribute, that is, the data points are closely related to the geographical location. In different databases, the data required for the construction of geological models are obtained. The required geological data include the three-dimensional distribution of the geology of the relevant areas of the tunnel or tunnel project, the uniaxial compressive strength of the rock mass, the rock mass quality index, the rock weathering condition, the groundwater condition and the rock mass geomechanical classification index value, different distribution lithology and other physical parameters, and the relevant detection physical parameter image data. The big data mining method can adopt the existing method, which will not be repeated here.

[0027] In the processing module, the present invention uses LS-DYNA finite element analysis software to simulate the geological data. According to the geological data, the attributes of the relevant simulation object, i.e., the geological model, are set in the finite element software. The three-dimensional model includes a geological model and a hydraulic blasting model. After the setting, the hydraulic blasting model is set in the geological model. The hydraulic blasting model and the geological model are meshed. After the meshing, the parameters of the relevant hydraulic blasting model, the calculation method of the relevant calculation model and the relevant parameters are set. The calculation model includes a mechanical model and a calculation model. The hydraulic blasting model uses an open cylindrical structure for hydraulic blasting simulation. The material The concrete is plain, the structure is filled with water, the explosive bag is set as a spherical one, placed in the center of the structure, and the radius of the structure is set according to the preset size of the explosive bag. The hydraulic blasting model is set by the parameters in the blasting scheme such as the amount of explosives in the hydraulic blasting method to be simulated, the radius of the structure, etc. In the above content, the explosives, water and air are modeled using Euler grids, the units in the model use the calculation model of the multi-material ALE algorithm, the structure is modeled using Lagrangian grids, the calculation model between concrete and water uses a coupling model, and the finite element model is calculated using the existing numerical simulation method of hydraulic blasting, which will not be repeated here. It should also be noted that the simulation can be performed according to the existing model simulation method of hydraulic blasting, which is not limited here.

[0028] After the finite element model simulation calculation is completed, the relevant simulated model is evaluated to obtain the corresponding risk assessment results, wherein the content of the risk assessment is mainly evaluated by evaluating the destructiveness of different spatial dimensions of the expanded range of the blasting range in the geological simulation model.

[0029] In the processing module, the destructiveness of different spatial dimensions includes evaluation through related methods of plane, i.e. horizontal plane direction and vertical direction, to generate specific values ​​of horizontal damage index and vertical damage index. First, the horizontal plane or the plane parallel to the vertical direction is used as the dividing plane, and the overall damage range of the simulated model is divided into different horizontal areas. The final result is different model intervals parallel to the horizontal plane, until the range without damage at the bottom. First of all, the plane division method is mainly to evaluate the damage range at different levels, and the hydraulic blasting results are evaluated based on the proportion of the interval where the damage range is located. In the vertical evaluation, different grids are set in the horizontal plane, and the vertical area under each grid is evaluated, mainly to evaluate the vertical stability of the geology after the tunnel or tunnel engineering. The evaluation standard for damage is that the geological structure is damaged, such as the displacement or direct destruction of the current geological structure.

[0030] Specifically, firstly, the overall damage range of the model after simulation is counted. The overall damage range is the size area of ​​the range that originally needs to be blasted (the ideal blasting range area of ​​the hydraulic blasting scheme in the three-dimensional model) minus the expanded range of the blasting range required by the blasting scheme. The overall damage range is specifically the area in the test range of the model after simulation minus the range that originally needs to be blasted. The above test range is based on the range that originally needs to be blasted, and the length of the same center and different directions is expanded outward to 150% (this fixed ratio is greater than 130% and can be set manually), and the minimum cuboid can cover all the expanded geological model ranges. When the range after simulated blasting in the simulation model cannot completely cover the range that originally needs to be blasted, it is necessary to redesign the relevant technical solutions to meet the range that needs to be blasted. When the overall damage range is determined, in the simulated model, the overall damage range is cut at equal intervals by a surface parallel to the horizontal plane to generate horizontal intervals of different levels, and the size of the damage range in different horizontal intervals is statistically analyzed, wherein the horizontal interval is divided into a number of three-dimensional grids, the size of which is one thousandth of the current interval or is set by manual experience. The value of the damage range in the horizontal interval that is subsequently involved in the calculation, i.e., the horizontal damage range value, is expressed in the form of a proportion, and its value is the proportion of the grid area where the damage occurs to the overall range, and the horizontal weight under each horizontal interval is set, and the interval where the water pressure blasting point is located is the middle The blasting range is normally distributed, and the horizontal weights are allocated according to the normal distribution. Specifically, for example, it is divided into 7 intervals, and the water pressure blasting point is set in the fourth interval. The horizontal weights of the intervals from top to bottom are 0.05, 0.1, 0.2, 0.3, 0.2, 0.1, and 0.05 respectively. The above is an exemplary description. The number and weights of the horizontal intervals can also be adjusted according to manual experience and actual conditions. In the evaluation process of the horizontal intervals, the damage range of different horizontal intervals can be effectively evaluated, and the relevant weights can be set at the same time. The weights of different intervals can effectively characterize the damage range of the geological model under the horizontal plane of different levels.

[0031] In the process of division in the vertical direction, the vertical damage area is taken as the evaluation object. Specifically, a uniform grid is divided on the horizontal plane, and the grid size is set according to the actual situation. The corresponding area directly below the uniform grid, that is, the vertical interval, is subjected to damage statistics, ranging from the upper surface of the overall damage range to the lowest position, and the damage range is statistically calculated. Similarly, the vertical interval is divided into several three-dimensional grids, the size of which is one thousandth of the current interval or set according to manual experience. The damage range value in the vertical interval, that is, the vertical damage range value, is the proportion of the grid area with damage to the overall range. In the process of vertical interval weight allocation, an initial vertical weight is set, and the initial vertical weight is set to 0.1. The vertical interval and weight can also be adjusted according to manual experience and actual conditions. After the setting is completed, when the vertical damage range value is greater than a certain threshold and the intervals greater than the threshold are continuous, that is, there are multiple vertical damage range values ​​in adjacent vertical ranges that are also greater than a certain threshold, the initial vertical weight of the corresponding interval is fixed. Increase, the above threshold is 60% of the size of the interval range, and the threshold can also be adjusted according to manual experience and actual conditions; according to the number of times the vertical damage range value of the vertical interval is continuously greater than the threshold, the weight of the corresponding vertical interval is increased to realize the weight distribution of the vertical interval. For example, if the vertical damage range value in a vertical interval is greater than the threshold, and the vertical damage range value of the next interval vertical interval is greater than the threshold, the weights of the two intervals are all increased to the value after the initial weight is increased by a fixed value. If the damage range in the next interval is still greater than the threshold, the weights of the three intervals are all increased to the initial weight plus two fixed values, and so on until an interval with a vertical damage range value less than or equal to the threshold appears, so its continuous interval weight is the number of consecutive intervals × fixed value + initial vertical weight, where the fixed value can be set to one twentieth of the initial vertical weight, and the initial vertical weight is divided according to the number of intervals, such as being set to the inverse of the number of intervals, such as setting 100 intervals, the corresponding initial vertical weight can be set to 0.01. By continuously increasing the weight of the vertical interval, the weighted score of the vertical damage range value of the vertical area is increased to represent the damage degree of the continuous vertical area. When the damage degree is greater than the threshold continuously, it means that the damage degree of multiple continuous vertical areas is high, and more serious risks may occur.

[0032] After the weight rules for different intervals are set, calculations are performed based on the statistical results of different intervals. First, the vertical damage range values ​​of the horizontal intervals are statistically judged. The vertical damage range values ​​of different horizontal intervals are weighted and summed according to the horizontal weights of the corresponding horizontal intervals to obtain the final calculated horizontal damage index value. The vertical damage range values ​​of the vertical intervals are statistically analyzed. According to the above-mentioned continuous interval rules, continuous intervals are searched, and the weights in the vertical intervals are modified and adjusted. The vertical damage range values ​​of different vertical intervals are weighted and summed according to the adjusted vertical weights to obtain the final vertical damage index value.

[0033] In the evaluation module, in order to conduct relevant risk evaluation on the above-mentioned horizontal damage indicators and vertical damage indicators, the present invention evaluates the above-mentioned contents through a fuzzy evaluation method.

[0034] A fuzzy evaluation database is established, which includes horizontal damage index and vertical damage index. The horizontal damage index includes very high, high, medium and low, and the corresponding division intervals are (0.6, 1], (0.3, 0.6], (0.1, 0.3], [0, 0.1]; the vertical damage index includes very high, high, medium, low and very low, and the corresponding division intervals are (0.6, ∞), (0.4, 0.6], (0.2, 0.4], (0.1, 0.2], [0, 0.1]). The above two damage index values ​​are converted into fuzzy language values, namely very high-TH , high-H, medium-M, low-L and very low-TL. After the damage index values ​​are converted, they are input into the fuzzy evaluation library to make a fuzzy judgment on the risk of water pressure blasting and obtain the evaluation result of the risk of water pressure blasting. Before inputting the fuzzy evaluation library, the horizontal damage index values ​​and the vertical damage index values ​​are converted from the actual domain to the fuzzy domain according to the corresponding intervals mentioned above, so that the horizontal damage severity and the vertical damage severity can be effectively corresponded. At the same time, the parameters in the conversion process can also provide certain data support for risk assessment and management. The fuzzy evaluation library is shown in Table 1.

[0035] Table 1

[0036]

[0037] The horizontal damage severity and vertical damage severity are evaluated through the above fuzzy evaluation library to generate the risk level of hydraulic blasting.

[0038] After the risk level of the above-mentioned hydraulic blasting is determined, relevant operations are performed according to the risk. During operation, when the risk level of hydraulic blasting is low, it means that the risk of hydraulic blasting is low, causing less damage to the relevant area, and outputs the horizontal damage range and vertical damage range in the three-dimensional model and the corresponding index values ​​for relevant personnel to view; when the risk level of hydraulic blasting is medium, it means that the later risk of hydraulic blasting will be within the normal range of damage, and outputs the horizontal damage range and vertical damage range in the three-dimensional model and the corresponding index values ​​to remind relevant personnel whether they need to adjust the blasting plan; when the risk level of hydraulic blasting is high, the risk of hydraulic blasting is high. The risk level will be higher, and the horizontal damage range and vertical damage range in the three-dimensional model and the corresponding indicator values ​​will be output. Timely alarms will be issued to remind relevant personnel to optimize and adjust the water pressure blasting plan. It is not recommended to use this plan for blasting, and the optimized and adjusted plan will be judged, and risk assessment needs to be re-evaluated; when the risk level of road water pressure blasting is very high, the damage range of water pressure blasting is large and serious, and relevant personnel are required to redesign the water pressure blasting plan, and repeat the judgment through the above content according to the redesigned plan until it meets the normal value.

[0039] Through the above-mentioned technical scheme, the present invention uses a water pressure blasting risk assessment system to effectively determine the geological data of the tunnel or tunnel engineering by means of big data mining, and at the same time constructs a three-dimensional model based on the determined geological data, and then simulates and models the water pressure blasting after the construction. Through the simulation and the simulated model, the risk of water pressure blasting is assessed. In the present invention, different interval damage scores are set through an adaptive weight setting method, and an effective risk assessment of the damage index is performed through a simulation evaluation method. At the same time, the risk assessment provides a relevant theoretical basis for the subsequent actual operation of water pressure blasting in the tunnel or tunnel engineering, and has strong practicality.

[0040] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. The hydraulic blasting risk assessment system based on big data is characterized by: include: An acquisition module, a processing module and an evaluation module; wherein the acquisition module, the processing module and the evaluation module are connected in sequence; The acquisition module is used to acquire geological data of a tunnel or tunnel engineering project by a big data mining method, the processing module is used to construct a three-dimensional model according to the geological data, simulate the three-dimensional model according to the hydraulic blasting scheme, and acquire damage index values ​​according to the simulated model, and the evaluation module evaluates the hydraulic blasting risk according to the acquired damage index values ​​to obtain a hydraulic blasting risk evaluation result; In the processing module, the damage index value includes a horizontal damage index value and a vertical damage index value; In the processing module, the process of obtaining the horizontal damage index value includes: The overall damage range is divided into horizontal intervals to obtain different horizontal intervals; the overall damage range is the area after the test range area in the model after simulation is removed from the first range area, wherein the first range area is the ideal blasting range of the hydraulic blasting scheme in the three-dimensional model, and the test range area is a rectangular area that is expanded outward to a fixed ratio with the same center and in different directions of the first range area, and the entire expanded area is covered by the smallest rectangular area; The damage range of the horizontal interval is counted to obtain a horizontal damage range value, and the horizontal interval is weighted and calculated according to the weight distribution result to obtain a horizontal damage index value. In the processing module, the process of obtaining the vertical damage index value includes: The overall damage range is divided into vertical intervals to obtain different vertical intervals, the damage ranges of the vertical intervals are counted to obtain vertical damage range values, the weights of the vertical intervals are initially allocated, the damage range values ​​of the vertical intervals are threshold judged, the initially allocated weights are adjusted according to the threshold judgment results, and the vertical damage range values ​​are weighted and calculated according to the adjusted weights to obtain vertical damage index values; Adjusting the initially allocated weights includes: when there is a vertical interval with a damage range greater than a threshold value in a continuous vertical interval, the weight of the vertical interval is increased, wherein the weight of the continuous vertical interval is adjusted to the number of consecutive intervals greater than the threshold value × a fixed value + an initial vertical weight.

2. The system according to claim 1, characterized in that In the processing module, a three-dimensional model is constructed according to the geological data through finite element analysis software, and the three-dimensional model includes a geological model and a hydraulic blasting model. The hydraulic blasting model in the three-dimensional model is set according to the hydraulic blasting plan, and the three-dimensional model is simulated by a numerical simulation method of hydraulic blasting.

3. The system according to claim 1, characterized in that In the evaluation module, the risk of hydraulic blasting is evaluated according to the acquired damage index values ​​by using a fuzzy evaluation method.

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