Blasting operation control system and method based on Internet of Things

Abstract

The invention relates to the technical field of remote execution control, in particular to a blasting operation control system and method based on the Internet of Things, and the system comprises a vibration simulation analysis module, a risk level calculation module, an operation process planning module and a real-time abnormity response module. According to the method, shock wave propagation under various blasting conditions is simulated and analyzed, the safety distance is accurately predicted, blasting safety is improved, risk assessment and adjustment of project planning are achieved by integrating the geological structure, the climate condition and the building position, the sustainability and social responsibility of a project are enhanced, and the method is suitable for popularization and application. The operation condition of a target project is monitored in real time in combination with an Internet of Things sensor, blasting parameters are adjusted in real time or operation is stopped, accurate and dynamic operation control is provided, the personnel safety risk is effectively reduced, the operation efficiency is improved, the safety and economic benefits of blasting operation are enhanced, and the adverse effect on the environment is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of remote execution control, and in particular to a blasting operation control system and method based on the Internet of Things. Background Art

[0002] The field of remote execution control technology uses information and communication technology to remotely control the operation and management of equipment or systems, allowing users to monitor, adjust and manage a variety of equipment through the network without physical contact. It is applied to industrial automation, smart homes, and remote medical equipment management. It can instantly respond to changes in system status and update operating instructions in real time to ensure the optimization and security of system operation. Combined with real-time collection and analysis of data, it optimizes the decision-making process and improves the accuracy of operations, ensuring the security of transmitted data and the accuracy of instruction execution, efficient system response speed and fault recovery capabilities.

[0003] Among them, the blasting operation control system focuses on managing and controlling the blasting operation process, ensuring the safety and efficiency of the blasting operation, and accurately controlling the blasting parameters to adapt to various conditions on site, including the amount of explosives, ignition time and blasting sequence. It monitors the on-site conditions in real time, including vibration, sound, and temperature, and dynamically adjusts operations based on monitoring results. It sets blasting parameters, adjusts the explosion sequence, and starts blasting operations without contacting the blasting site. It is used in a variety of industries such as mining, construction, and demolition, effectively reducing personnel safety risks and improving work efficiency, helping to improve the safety and economic benefits of operations, and reducing the impact on the environment.

[0004] In actual operations, traditional blasting operation control systems have poor data processing speed and response timeliness. In scenarios that require real-time adjustment and precise control, they lack the ability to respond immediately to environmental changes, are unable to use real-time data for dynamic decision-making, and have difficulty accurately predicting and responding to emergencies. As a result, due to sudden changes in the environment, operating parameters cannot be adjusted in a timely manner, leading to safety accidents, including poor explosion effects or safety accidents, affecting the safety and efficiency of blasting operations, increasing safety risks, reducing operating efficiency, and causing unnecessary damage to the environment. When dealing with complex and dynamically changing environmental conditions, it affects operational safety and economic benefits. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a blasting operation control system and method based on the Internet of Things.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: A blasting operation control system based on the Internet of Things comprises: The vibration simulation analysis module is based on the simulated blasting condition data set. By setting a variety of blasting conditions, it simulates and calculates the propagation range of the vibration wave, analyzes the safety distance under a variety of blasting conditions, and generates the safety distance calculation results. The risk level calculation module collects the geological structure, climate conditions, and building location information of the target blasting project location based on the safety distance calculation result, evaluates the impact of the target project on environmental conditions, calculates the environmental damage risk score, and calculates the risk level of the target blasting project by evaluating the impact of various environmental conditions on blasting risks, thereby generating a project risk assessment result; The operation process planning module calculates the amount of explosives required for the target blasting project based on the project risk assessment results, plans multiple processes of the blasting operation, and generates operation parameter configuration results; The real-time abnormal response module is based on the operation parameter configuration results and uses the Internet of Things sensors to monitor the vibration, slope stability, and toxic and harmful gas concentration data of the target location in real time. By detecting abnormal data, it evaluates the impact of abnormal data on the blasting project, adjusts the blasting operation, and generates abnormal condition response records.

[0007] As a further solution of the present invention, the step of obtaining the propagation range of the shock wave is specifically as follows: Based on the simulated blasting condition data set, set various blasting conditions, including explosive quantity, explosive type, geological conditions, and generate a list of setting parameters; Based on the set parameter list, using the set explosive amount and type of explosive, the energy generated by the explosion of the explosive is calculated to generate energy release data; Based on the energy release data, by the formula: ; Calculate the propagation range of the shock wave; Where E is the explosion energy, is the density of the geological medium, S is the surface area, is the attenuation coefficient, and R is the propagation range of the shock wave.

[0008] As a further solution of the present invention, the step of obtaining the safety distance calculation result is specifically as follows: Based on the propagation range of the shock wave, by analyzing the influence of various geological types and building designs on the shock wave response, including considering the height and seismic performance of the building, the type of surface rock and soil, evaluating the safety margin required in various situations, and obtaining the safety margin analysis results; Based on the safety margin analysis results, the formula is: ; Calculate the safety distance and obtain the calculation result of the safety distance; Where D is the safety distance, is the maximum vibration wave propagation range, is the vibration risk factor, is the structural safety distance, and F is the safety factor.

[0009] As a further solution of the present invention, the steps for obtaining the environmental damage risk score are specifically as follows: Based on the safety distance calculation result, the target blasting project information is analyzed, and the geological structure, climate conditions, and building location information of the blasting location are collected to generate a project condition data set; Based on the project condition data set, through the formula: ; Calculate geological stability coefficients for multiple locations; Among them, FS is the safety factor, c is the effective cohesion of the soil, A is the area of ​​the landslide surface, is the inclination angle between the landslide surface and the horizontal plane, W is the weight of the landslide body, is the internal friction angle of the soil; Based on the geological stability coefficient, the risks of soil loosening, crack expansion, landslide and collapse in multiple locations are analyzed and identified, the impact of the target blasting operation project on environmental damage is evaluated, and the environmental damage risk score is calculated.

[0010] As a further solution of the present invention, the steps for obtaining the project risk assessment results are specifically as follows: Based on the environmental damage risk score, evaluate the impact of various conditions on blasting risk, including geological structure, climate conditions, and safe distance of buildings, and generate analysis results of influencing factors; Based on the analysis results of the influencing factors, the formula is: ; Calculate risk scores for target blasting projects; in, is the basic risk shift, is the weight coefficient of geological structure, G is the geological structure score, is the weight coefficient of climate conditions, H is the climate condition score, is the weight coefficient of building safety distance, J is the safety distance score; Based on the risk score of the target blasting project, the risk level of the engineering project is evaluated, and according to the evaluation result, the project plan is adjusted, including terminating the project or adjusting the blasting working parameters, to obtain the project risk assessment result.

[0011] As a further solution of the present invention, the step of obtaining the operation parameter configuration result is specifically: Based on the project risk assessment results, through the formula: ; Calculate the required amount of explosives and obtain the project explosives quantity information; Among them, BV represents the volume of the blasting area, RF is the rock factor, is the rock crack density coefficient, is the blasting depth adjustment coefficient, E is the relative TNT equivalent of the explosive, and Q represents the calculated total amount of explosives; Based on the explosive quantity information of the project, the blasting ignition sequence is planned taking into account the explosive quantity and the layout of the blasting points, and the ignition sequence configuration is generated; Based on the ignition sequence configuration, the continuity and safety of the blasting operation are taken into consideration, the blasting interval is set, the execution effect of the blasting process is optimized, and the operation parameter configuration result is generated.

[0012] As a further solution of the present invention, the step of obtaining the abnormal condition response record is specifically: Based on the operation parameter configuration results, the vibration, slope stability, and toxic and harmful gas concentration data of the target location are monitored in real time through the Internet of Things sensor to generate real-time monitoring data records; Based on the real-time monitoring data records, using the formula: ; Calculate the anomaly index; in, is the abnormal index at time point t, j is the index of the monitoring data type, m is the number of types of monitoring data, is the importance weight of the jth data type, k is the time window size, is the weight of the i-th data point in the time window, is the jth data at time point The deviation between the data and the preset threshold, t is the current time point, i is the index in the time window; Based on the abnormal index, by analyzing the abnormal degree of monitoring data at multiple time points and the impact on the blasting project, the blasting operation is adjusted, including adjusting the blasting operation waiting time and the release signal sending time, and generating an abnormal condition response record.

[0013] A blasting operation control method based on the Internet of Things, the blasting operation control method based on the Internet of Things is executed based on the above-mentioned blasting operation control system based on the Internet of Things, and comprises the following steps: S1: Based on the simulated blasting condition data set, by simulating the blasting process under various conditions, the propagation range of the shock wave is calculated, and the safety distance required for various blasting conditions is identified, and the safety distance calculation results are generated; S2: Based on the safety distance calculation result, collect the geological, climate, and building location information of the target project location, analyze the environmental damage risk of the target project, evaluate the risk level of the target blasting project, and generate a project risk assessment result; S3: Based on the project risk assessment results, the amount of explosives required for the target project is calculated, and multiple processes of blasting operations are planned, including configuring blasting sequences and time intervals, and generating operation parameter configuration results; S4: Based on the operation parameter configuration results, the vibration, slope stability, and toxic and harmful gas concentration data of the blasting location are monitored in real time through the Internet of Things sensors, abnormal data are detected and the blasting operation is adjusted, including adjusting the blasting operation waiting time and the release signal sending time, and generating abnormal condition response records.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by simulating and analyzing the propagation of shock waves under various blasting conditions, the safe distance is accurately predicted, and the safety of blasting is improved. By integrating geological structure, climatic conditions, and building locations, risk assessment and adjustment of project planning are achieved, and the sustainability and social responsibility of the project are enhanced. In combination with the Internet of Things sensors, the operating conditions of the target project are monitored in real time, and the blasting parameters are adjusted or the operation is terminated in real time, providing precise and dynamic operation control, effectively reducing personnel safety risks and improving operation efficiency, enhancing the safety and economic benefits of blasting operations, and reducing adverse impacts on the environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a system flow chart of the present invention; Figure 2 A flow chart of calculating the propagation range of shock waves of the present invention; Figure 3 A flow chart of obtaining the calculation result of the safety distance of the present invention; Figure 4 A flowchart of computing environment destruction risk scoring of the present invention; Figure 5 A flow chart of obtaining project risk assessment results of the present invention; Figure 6 A flowchart of obtaining the configuration result of the operation parameters of the present invention; Figure 7 The present invention is a flowchart for obtaining abnormal condition response records. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0017] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0018] See also Figure 1 The present invention provides a technical solution, a blasting operation control system based on the Internet of Things, comprising: The vibration simulation analysis module is based on the simulated blasting condition data set. By setting a variety of blasting conditions, it simulates and calculates the propagation range of the vibration wave, analyzes the safety distance under a variety of blasting conditions, and generates the safety distance calculation results. The risk level calculation module collects the geological structure, climate conditions, and building location information of the target blasting project location based on the safety distance calculation results, evaluates the impact of the target project on environmental conditions, calculates the environmental damage risk score, and calculates the risk level of the target blasting project by evaluating the impact of various environmental conditions on blasting risks, generating project risk assessment results; The operation process planning module calculates the amount of explosives required for the target blasting project based on the project risk assessment results, plans multiple processes of the blasting operation, and generates the operation parameter configuration results; The real-time abnormal response module is based on the operation parameter configuration results. It monitors the vibration, slope stability, and toxic and harmful gas concentration data of the target location in real time through the Internet of Things sensors. By detecting abnormal data, it evaluates the impact of abnormal data on the blasting project, adjusts the blasting operation, and generates abnormal condition response records.

[0019] The safety distance calculation results include vibration propagation speed, impact area calculation results, and vibration wave propagation path. The project risk assessment results include environmental damage probability calculation results, project risk level, and multi-factor impact degree information. The operation parameter configuration results include explosive demand calculation data, blasting interval time, and operation process schedule. The abnormal condition response records include abnormal type information, abnormal data impact assessment results, and adjustment measure execution records.

[0020] See also Figure 2 , the steps for obtaining the propagation range of the shock wave are as follows: Based on the simulated blasting condition data set, set various blasting conditions, including explosive quantity, explosive type, geological conditions, and generate a list of setting parameters; The blasting parameters are set and adjusted through computer simulation, including the type and quantity of explosives and simulated geological conditions. The geological condition simulation parameters include rock type, density and humidity, etc. Simulation software such as ANSYS or AutoCAD is used to input parameters and set scenes to ensure that the simulation environment can reflect different blasting settings. The collected data is organized into a set parameter list to provide the necessary basic data for subsequent energy calculations and risk assessments.

[0021] Based on the set parameter list, using the set explosive quantity and type of explosive, the energy generated by the explosion of the explosive is calculated to generate energy release data; Computer simulation is used to predict the energy released when explosives explode. The process is executed by inputting the type, quantity and geological simulation conditions of explosives into the energy calculation model. The energy release amount is estimated based on the chemical reaction properties of the explosives and the characteristics of geological conditions using the thermodynamic energy equation. The calculation process includes the reaction heat of the explosives and the gas generation rate, and takes into account environmental factors, including the heat absorption characteristics of rocks, to generate energy release data, which provides a scientific basis for subsequent operations such as blasting planning and safety assessment.

[0022] Based on the energy release data, the formula: ; Calculate the propagation range of the shock wave; Where E is the explosion energy, which represents the total energy released in the explosion event. is the density of the geological medium, reflecting the density of the geological environment, S is the surface area, reflecting the actual area of ​​the blasting area, is the attenuation coefficient, which reflects the attenuation effect of geological conditions on vibration propagation, and R is the propagation range of the vibration wave.

[0023] formula: ; Parameter meaning and acquisition method: E is the total energy released by the explosion; is the density of geological medium; S is the surface area; is the attenuation coefficient, which describes the attenuation effect of geological conditions on vibration propagation; Calculation example: Set the blasting charge to release the energy of the explosive , geological medium density , surface area , attenuation coefficient , calculate the propagation range of the shock wave: ; ; ; ; Calculation results It shows that under given blasting conditions and geological environment, the propagation range of the shock wave is about 59.5 meters, reflecting the propagation distance of the shock wave under target conditions. The calculation process is used to predict potential dangerous areas of large-scale blasting activities, providing an important basis for the formulation of safety measures.

[0024] See also Figure 3 , the specific steps for obtaining the safety distance calculation results are: Based on the propagation range of the seismic wave, the impact of various geological types and building designs on the seismic wave response is analyzed, including the height and seismic performance of the building, the type of surface rock and soil, and the safety margin required in various situations are evaluated to obtain the safety margin analysis results; Use seismic wave propagation models, such as SEISMIC-HP software, to simulate the behavior of seismic waves under different geological conditions. The input parameters include the physical properties of the surface rock and soil, such as rock type, density and shock absorption characteristics, and the structural parameters of the building, including height, building materials and seismic design standards. The impact of the building due to seismic waves is analyzed, and the safety margin required in various situations is evaluated in combination with the seismic performance of the building. During the calculation process, the simulation parameters are adjusted according to the height and seismic resistance of the building, and the vibration propagation is calculated to ensure an accurate assessment of the safety margin. The generated safety margin analysis results list the safe distances under different geological and building conditions, providing a scientific basis for the subsequent safety planning of blasting operations.

[0025] Based on the safety margin analysis results, the formula is: ; Calculate the safety distance and obtain the calculation result of the safety distance; Where D is the safety distance, is the maximum vibration wave propagation range, is the vibration risk factor, indicating the influence of geological conditions on vibration propagation. is the structural safety distance, and F is the safety factor, which reflects the safety margin.

[0026] formula: ; Parameter meaning and acquisition method: D: safe distance; : Maximum shock wave propagation range; : Vibration risk factor, obtained according to the geological type and the design seismic resistance level of the building; : Structural safety distance, based on the stability and earthquake-resistant design of the building; F: safety factor, reflecting the safety margin; Calculation example: set up =300 m, =1.1, =50 meters, F=20 meters, calculate the safe distance: ; ; ; ; The calculated result D = 377 meters shows that under the given blasting conditions and safety considerations, the safe distance is at least 377 meters. The result is used to ensure the safety of personnel and equipment.

[0027] See also Figure 4 , the specific steps for obtaining environmental damage risk scores are: Based on the safety distance calculation results, analyze the target blasting project information, collect the geological structure, climate conditions, and building location information of the blasting location, and generate a project condition data set; Using geographic information system software and environmental impact assessment tools such as ArcGIS and SimaPro, geological data including soil type, rock structure, climate data such as average temperature, rainfall and wind speed, and regional building information including building safety distance are input. Through comprehensive analysis of multiple information, a project condition dataset containing all relevant conditions is generated. This dataset records all key factors that affect blasting planning and execution, ensuring that all operations are carried out within legal and safe ranges.

[0028] Based on the project condition data set, through the formula: ; Calculate geological stability coefficients for multiple locations; Among them, FS is the safety factor, which is used to measure the stability of the geological structure of the slope or blasting area, c is the effective cohesion of the soil, which reflects the bonding strength between soil particles, A is the area of ​​the landslide surface, is the inclination angle between the landslide surface and the horizontal plane, W is the weight of the landslide body, is the internal friction angle of the soil.

[0029] formula: ; Parameter meaning and acquisition method: FS is the safety factor, which measures the slope stability and is calculated using geological and structural data; c is soil cohesion, which reflects the adhesion characteristics between soil particles; A is the contact area, reflecting the actual area of ​​the landslide surface; is the inclination angle of the landslide surface, reflecting the angle between the landslide surface and the horizontal plane; W is the weight of the landslide mass, taking into account the moisture content of the soil and the type of material; is the internal friction angle, which represents the friction resistance between soil particles; Calculation example: Set c=0.3kN / m2, A=500m2, =30°,W=15000kN, =25°, calculate the safety factor: ; ; ; ; ; Calculation results It shows that the slope is unstable under the current conditions, indicating that the target location has a potential landslide risk. The calculation process is used to evaluate the impact of blasting activities on the geological risks of the surrounding environment and provide a basis for taking corresponding safety measures.

[0030] Based on the geological stability coefficient, analyze and identify the risks of soil loosening, crack expansion, landslide and collapse in multiple locations, evaluate the impact of the target blasting operation project on environmental damage, and calculate the environmental damage risk score; Using geological risk assessment models, such as SLIDE or ROCKFALL software, input parameters such as soil type, soil moisture, terrain inclination, etc., simulate possible geological displacement and crack development, identify high-risk areas through the model's calculation results, and conduct an environmental damage risk assessment for each area. The calculated environmental damage risk score is based on soil stability and known geological sensitive points, providing blasting engineers with environmental protection measures that should be considered when performing blasting.

[0031] See also Figure 5 , the specific steps for obtaining project risk assessment results are: Based on the environmental damage risk score, evaluate the impact of various conditions on blasting risk, including geological structure, climate conditions, and safe distance of buildings, and generate analysis results of influencing factors; A multi-parameter risk analysis model is used, such as the risk assessment software Crystal Ball. The model integrates multiple risk factors, including the complexity of geological structure, uncertainty of climatic conditions, and safety standards of building distances. By inputting target parameters, the model calculates the degree of influence of each factor on blasting safety. During the assessment process, the model uses probability distribution and simulation technology to predict the blasting risk level under different conditions. The influencing factor analysis results generated by the system list the specific contribution of each condition to the blasting risk, providing a comprehensive risk view.

[0032] Based on the analysis results of influencing factors, the formula is: ; Calculate risk scores for target blasting projects; in, is the basic risk shift, is the weight coefficient of geological structure, G is the geological structure score, is the weight coefficient of climate conditions, H is the climate condition score, is the weight coefficient of building safety distance, and J is the safety distance score.

[0033] formula: ; Parameter meaning and acquisition method: : Basic risk deviation, representing the baseline risk level; : Weight coefficient of geological structure, determined based on statistical data and expert evaluation of the impact of geological stability on safety; G: geological structure score, obtained through analysis of geological survey information; : The weight coefficient of climate conditions is determined based on the analysis of historical climate data and its impact on project safety; H: climate condition score, obtained by analyzing long-term meteorological records; : The weight coefficient of the safety distance is determined based on safety regulations and accident data analysis; J: Safety distance score, based on field measurements and safety standards assessment; Calculation example: set up =0.5, =0.3, G=0.8, =0.2, H=0.6, =0.1, J=0.9, Calculate the risk score: ; ; ; Formula calculation results: Calculation results It indicates that the project has a medium risk level. The calculation process is used to develop and adjust the project risk management strategy to ensure that the project meets safety requirements.

[0034] Based on the risk score of the target blasting project, the risk level of the engineering project is evaluated, and according to the evaluation results, the project plan is adjusted, including terminating the project or adjusting the blasting working parameters, to obtain the project risk assessment results; Use a project risk assessment model, such as the risk management tool Riskalyze. The model comprehensively considers known risk scores and project-specific parameters, including the type and quantity of explosives required for blasting and the scheduled time of blasting. The model analysis is based on the risk score and the specific needs of the project, assesses the possible risk level, and makes project adjustment suggestions based on the assessment results, including whether to terminate the project or adjust blasting parameters to reduce risks. The assessment process ensures that project decisions are based on the latest risk data, and generates project risk assessment results based on the assessment results, including recommended operational adjustments, to ensure project safety.

[0035] See also Figure 6 , the specific steps for obtaining the job parameter configuration results are: Based on the project risk assessment results, the formula is: ; Calculate the required amount of explosives and obtain the project explosives quantity information; Among them, BV represents the volume of the blasting area, and RF is the rock factor, which reflects the hardness and resistance of the rock. is the rock crack density coefficient, which reflects the distribution of cracks inside the rock. is the blasting depth adjustment coefficient, which reflects the impact of blasting depth on explosive demand, E is the relative TNT equivalent of explosives, which is used to adjust the performance differences between different explosives, and Q represents the calculated total amount of explosives.

[0036] formula: ; Parameter meaning and acquisition method: BV: is the volume of the blasting area, which is calculated by combining the on-site survey data with the regional geometric parameters, and reflects the physical space that needs to be processed by blasting; RF: Rock factor, obtained through rock mechanics testing, reflects the hardness and blasting resistance of the rock; : is the rock crack density coefficient, which is obtained through geological survey and rock crack distribution statistics, reflecting the influence of rock crack density on blasting energy demand; : It is the blasting depth adjustment coefficient, which is obtained by adjusting the blasting depth parameters provided by the engineering design, and reflects the impact of blasting depth on the demand for explosives; E: is the relative TNT equivalent of the explosive, obtained from the instructions provided by the explosive manufacturer and used to adjust for differences in explosive performance; Calculation example: Set BV=1000, RF=1.2, =0.8, =1.3, E=0.9, calculate the amount of explosives required: ; ; The calculation result Q=1386.67 shows that the mass of explosives required for the blasting operation is 1386.67 kg. The value reflects the impact of the volume of the blasting area, rock hardness, crack density, blasting depth and explosive efficiency on the demand for explosives. The formula is used to calculate the amount of explosives required for blasting to ensure the blasting effect and safety.

[0037] Based on the explosive quantity information of the project, the blasting ignition sequence is planned and the ignition sequence configuration is generated by considering the explosive quantity and the layout of the blasting points; Use blasting design software Blastware or BlastPlan, input the explosive type and explosive quantity data for each blasting point, and calculate the best ignition sequence based on the spatial layout of the blasting points. The calculation takes into account the interaction between different blasting points and the potential risk impact to ensure the continuity of the blasting process and maximize the effect. The generated ignition sequence configuration clearly indicates the ignition time and order of each blasting point.

[0038] Based on the ignition sequence configuration, considering the continuity and safety of the blasting operation, the blasting interval is set, the execution effect of the blasting process is optimized, and the operation parameter configuration results are generated; Use the blasting simulation and optimization tools DyNOpt or ExploSim to input the ignition sequence data, analyze the continuity and safety of the blasting operation, and automatically adjust the blasting interval time to ensure that there is enough interval between each blast to dissipate the vibration and pressure waves generated, avoid safety accidents caused by too short intervals between adjacent blasting, ensure the accuracy of the operation, and improve the safety and efficiency of the entire blasting operation. The optimized blasting process allows for smoother and more controllable execution, reducing unexpected and unplanned downtime.

[0039] See also Figure 7 , the specific steps for obtaining abnormal condition response records are: Based on the operation parameter configuration results, the vibration, slope stability, and toxic and harmful gas concentration data of the target location are monitored in real time through IoT sensors, and real-time monitoring data records are generated; IoT sensors are deployed at the target location to monitor the vibration, slope stability, and toxic and harmful gas concentration data of the target location in real time. The sensors are connected to the central data processing system, such as the IoT platform ThingSpeak or IBM WatsonIoT. The data collected by the sensors are sent to the target platform in real time. Data stream processing technology such as Apache Kafka is used to process the target high-speed data stream to ensure that the data received from each sensor can be analyzed in real time. The target real-time data records the vibration intensity, rock surface displacement, slope stability, water seepage and leakage, and toxic and harmful gas concentration information of each measuring point, allowing the operation team to understand the on-site conditions in real time.

[0040] Based on real-time monitoring data records, using the formula: ; Calculate the anomaly index; in, is the abnormal index at time point t, reflecting the degree of abnormality after integrating various monitoring data, j is the index of the monitoring data type, m is the number of types of monitoring data, is the importance weight of the jth data type, k is the time window size, is the weight of the i-th data point in the time window, is the jth data at time point The deviation between the data and the preset threshold, t is the current time point, and i is the index in the time window.

[0041] formula: ; Parameter meaning and acquisition method: : The abnormality index at time point t, used to measure the degree of abnormality; j: index of monitoring data type, representing different types of data, including vibration, slope stability, and toxic and harmful gas concentration data; : The importance weight of the jth data type, which is used to adjust the influence of different data types in the anomaly index; k: time window size, preset according to monitoring frequency and required data sensitivity; : The weight of the i-th data point in the time window, assigned according to time proximity; :The jth data at time point The difference between the value and the preset threshold is obtained by comparing the real-time data with the threshold; t: current time point, indicating the specific moment of evaluating the anomaly; i: index within the time window; Calculation example: m=3 is set to reflect that three types of data are considered, including vibration, slope stability, and toxic and hazardous gas concentration data. k=5 means that data at five time points are considered. , , , , , , , calculate the anomaly index: ; ; ; Calculation results =0.14 indicates that at the current time point, after comprehensively considering the three types of monitoring data, the anomaly index is 0.14. The value reflects the degree of anomaly detected by the system under given weights and data deviations. The calculation process is used to decide whether it is necessary to adjust the blasting operation or take response measures, thereby ensuring the safety of the blasting operation and preventing and reducing operational risks.

[0042] Based on the abnormal index, by analyzing the abnormal degree of monitoring data at multiple time points and the impact on the blasting project, the blasting operation is adjusted, including adjusting the blasting operation waiting time and the release signal sending time, and generating abnormal condition response records; Use the statistical analysis software R or the Pandas library in Python to calculate the standard deviation and coefficient of variation of the data, determine the degree of abnormality of the data by comparing it with the predetermined safety threshold, analyze the abnormal indicators of the data, and combine decision trees or machine learning algorithms to adjust the waiting time for blasting operations and the time to send the release signal. The target adjustment is based on real-time data and preset response protocols to minimize risks and ensure personnel safety. Each adjustment will be recorded in the abnormal condition response record to ensure that safety measures can be traced and generate abnormal condition response records.

[0043] A blasting operation control method based on the Internet of Things, the blasting operation control method based on the Internet of Things is executed based on the above-mentioned blasting operation control system based on the Internet of Things, and comprises the following steps: S1: Based on the simulated blasting condition data set, by simulating the blasting process under various conditions, the propagation range of the shock wave is calculated, and the safety distance required for various blasting conditions is identified, and the safety distance calculation results are generated; S2: Based on the safety distance calculation results, collect the geological, climate, and building location information of the target project location, analyze the environmental damage risk of the target project, evaluate the risk level of the target blasting project, and generate the project risk assessment results; S3: Based on the project risk assessment results, calculate the amount of explosives required for the target project and plan multiple processes of blasting operations, including configuring blasting sequences and time intervals, and generating operation parameter configuration results; S4: Based on the operation parameter configuration results, the IoT sensors are used to monitor the vibration, slope stability, and toxic and harmful gas concentration data of the blasting location in real time, detect abnormal data and adjust the blasting operation, including adjusting the blasting operation waiting time and the release signal sending time, and generating abnormal condition response records.

[0044] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A blasting operation control system based on the Internet of Things, characterized in that: The system comprises: The vibration simulation analysis module is based on the simulated blasting condition data set. By setting a variety of blasting conditions, it simulates and calculates the propagation range of the vibration wave, analyzes the safety distance under a variety of blasting conditions, and generates the safety distance calculation results. The risk level calculation module collects the geological structure, climate conditions, and building location information of the target blasting project location based on the safety distance calculation result, evaluates the impact of the target project on environmental conditions, calculates the environmental damage risk score, and calculates the risk level of the target blasting project by evaluating the impact of various environmental conditions on blasting risks, thereby generating a project risk assessment result; The operation process planning module calculates the amount of explosives required for the target blasting project based on the project risk assessment results, plans multiple processes of the blasting operation, and generates operation parameter configuration results; The real-time abnormal response module is based on the operation parameter configuration results and uses the Internet of Things sensors to monitor the vibration, slope stability, and toxic and harmful gas concentration data of the target location in real time. By detecting abnormal data, it evaluates the impact of abnormal data on the blasting project, adjusts the blasting operation, and generates abnormal condition response records.

2. The blasting operation control system based on the Internet of Things according to claim 1 is characterized in that: The steps for obtaining the propagation range of the shock wave are specifically as follows: Based on the simulated blasting condition data set, set various blasting conditions, including explosive quantity, explosive type, geological conditions, and generate a list of setting parameters; Based on the set parameter list, using the set explosive quantity and type of explosive, the energy generated by the explosion of the explosive is calculated to generate energy release data; Based on the energy release data, by the formula: ； Calculate the propagation range of the shock wave; Where E is the explosion energy, is the density of the geological medium, S is the surface area, is the attenuation coefficient, and R is the propagation range of the shock wave.

3. The blasting operation control system based on the Internet of Things according to claim 2 is characterized in that: The steps for obtaining the safety distance calculation result are specifically as follows: Based on the propagation range of the shock wave, by analyzing the influence of various geological types and building designs on the shock wave response, including considering the height and seismic performance of the building, the type of surface rock and soil, evaluating the safety margin required in various situations, and obtaining the safety margin analysis results; Based on the safety margin analysis results, the formula is: ； Calculate the safety distance and obtain the safety distance calculation result; Where D is the safety distance, is the maximum vibration wave propagation range, is the vibration risk factor, is the structural safety distance, and F is the safety factor.

4. The blasting operation control system based on the Internet of Things according to claim 1 is characterized in that: The steps for obtaining the environmental damage risk score are specifically as follows: Based on the safety distance calculation result, the target blasting project information is analyzed, and the geological structure, climate conditions, and building location information of the blasting location are collected to generate a project condition data set; Based on the project condition data set, through the formula: ； Calculate geological stability coefficients for multiple locations; Among them, FS is the safety factor, c is the effective cohesion of the soil, A is the area of ​​the landslide surface, is the inclination angle between the landslide surface and the horizontal plane, W is the weight of the landslide body, is the internal friction angle of the soil; Based on the geological stability coefficient, the risks of soil loosening, crack expansion, landslide and collapse in multiple locations are analyzed and identified, the impact of the target blasting operation project on environmental damage is evaluated, and the environmental damage risk score is calculated.

5. The blasting operation control system based on the Internet of Things according to claim 4 is characterized in that: The specific steps for obtaining the project risk assessment results are: Based on the environmental damage risk score, evaluate the impact of various conditions on blasting risk, including geological structure, climate conditions, and safe distance of buildings, and generate analysis results of influencing factors; Based on the analysis results of the influencing factors, the formula is: ； Calculate risk scores for target blasting projects; in, is the basic risk shift, is the weight coefficient of geological structure, G is the geological structure score, is the weight coefficient of climate conditions, H is the climate condition score, is the weight coefficient of building safety distance, J is the safety distance score; Based on the risk score of the target blasting project, the risk level of the engineering project is evaluated, and according to the evaluation result, the project plan is adjusted, including terminating the project or adjusting the blasting working parameters, to obtain the project risk assessment result.

6. The blasting operation control system based on the Internet of Things according to claim 1 is characterized in that: The steps for obtaining the job parameter configuration result are specifically as follows: Based on the project risk assessment results, through the formula: ； Calculate the required amount of explosives and obtain the project explosives quantity information; Among them, BV represents the volume of the blasting area, RF is the rock factor, is the rock crack density coefficient, is the blasting depth adjustment coefficient, E is the relative TNT equivalent of the explosive, and Q represents the calculated total amount of explosives; Based on the explosive quantity information of the project, the blasting ignition sequence is planned taking into account the explosive quantity and the layout of the blasting points, and the ignition sequence configuration is generated; Based on the ignition sequence configuration, the continuity and safety of the blasting operation are taken into consideration, the blasting interval is set, the execution effect of the blasting process is optimized, and the operation parameter configuration result is generated.

7. The blasting operation control system based on the Internet of Things according to claim 1 is characterized in that: The specific steps of obtaining the abnormal condition response record are: Based on the operation parameter configuration results, the vibration, slope stability, and toxic and harmful gas concentration data of the target location are monitored in real time through the Internet of Things sensor to generate real-time monitoring data records; Based on the real-time monitoring data records, using the formula: ； Calculate the anomaly index; in, is the abnormal index at time point t, j is the index of the monitoring data type, m is the number of types of monitoring data, is the importance weight of the j-th data type, k is the time window size, is the weight of the i-th data point in the time window, is the jth data at time point The deviation between the data and the preset threshold, t is the current time point, i is the index in the time window; Based on the abnormal index, by analyzing the abnormal degree of monitoring data at multiple time points and the impact on the blasting project, the blasting operation is adjusted, including adjusting the blasting operation waiting time and the release signal sending time, and generating an abnormal condition response record.

8. A blasting operation control method based on the Internet of Things, characterized in that: The blasting operation control system based on the Internet of Things according to any one of claims 1 to 7 comprises the following steps: S1: Based on the simulated blasting condition data set, by simulating the blasting process under various conditions, the propagation range of the shock wave is calculated, and the safety distance required for various blasting conditions is identified, and the safety distance calculation results are generated; S2: Based on the safety distance calculation result, collect the geological, climate, and building location information of the target project location, analyze the environmental damage risk of the target project, evaluate the risk level of the target blasting project, and generate a project risk assessment result; S3: Based on the project risk assessment results, the amount of explosives required for the target project is calculated, and multiple processes of blasting operations are planned, including configuring blasting sequences and time intervals, and generating operation parameter configuration results; S4: Based on the operation parameter configuration results, the vibration, slope stability, and toxic and harmful gas concentration data of the blasting location are monitored in real time through the Internet of Things sensors, abnormal data are detected and the blasting operation is adjusted, including adjusting the blasting operation waiting time and the release signal sending time, and generating abnormal condition response records.

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