Blasting vibration monitoring method and system based on vision and vibration sensors

Abstract

The invention discloses a blasting vibration monitoring method and system based on vision and vibration sensors, and relates to the technical field of blasting vibration monitoring. An aerial vision monitoring device is arranged at a set height right above a blasting point, and a vibration sensor array is radially arranged around the blasting point; and the visual monitoring device and the vibration sensor array are in wireless communication connection with the blasting vibration analysis module based on the computer. Omnibearing monitoring of the blasting process is achieved by combining the aerial vision monitoring device and the ground vibration sensor array, ground vibration data can be captured, and the scattering condition of fragments generated by explosion can be observed. An image feature recognition algorithm is used for analyzing an image captured by a high-speed camera, and visual evidence is provided for understanding the explosion effect. Complex vibration data and visual feature changes can be converted into charts and schematic diagrams which are easy to understand through image processing software and a data visualization tool, and non-professionals can conveniently and rapidly grasp key information.

Description

Technical Field

[0001] The present invention relates to the technical field of blasting vibration monitoring, and particularly to a blasting vibration monitoring method and system based on vision and vibration sensors. Background Art

[0002] Blasting vibration monitoring technology is mainly used to evaluate and control the impact of blasting operations on the surrounding environment and buildings. The existing technologies mainly include the following directions: Seismograph monitoring: Measuring the seismic waves generated by blasting through a seismograph and analyzing parameters such as vibration intensity and frequency. Accelerometer monitoring: Installing accelerometers on buildings or the ground to collect blasting vibration data in real time. Microseismic monitoring: Using highly sensitive sensors to monitor the changes in microseismic signals during the blasting process.

[0003] The technical defects of the above traditional blasting vibration monitoring technologies are as follows: The monitoring ranges of seismographs and accelerometers are small, making it difficult to cover a large area and hard to reflect the overall vibration situation around the blasting point. During the blasting process, simply conducting vibration monitoring is not enough. For some blasting-related characteristics, such as crushed stones, without monitoring, it is difficult to understand the trajectories, speeds, etc. of the high-speed crushed stones generated by blasting, and the additional destructiveness caused by blasting cannot be controlled. Summary of the Invention

[0004] To solve the above technical problems, the present invention provides a blasting vibration monitoring method and system based on vision and vibration sensors. The following technical solutions are adopted: A blasting vibration monitoring method based on vision and vibration sensors. An aerial vision monitoring device is arranged at a set height directly above the blasting point, and a vibration sensor array is arranged radially around the blasting point. The vision monitoring device and the vibration sensor array are wirelessly communicatively connected to a computer-based blasting vibration analysis module. The monitoring method for the blasting vibration process includes the following steps: Step 1: Start all the blasting vibration monitoring intelligent sensors of the vibration sensor array and start the high-speed camera of the aerial vision monitoring device. Perform time synchronization on all the blasting vibration monitoring intelligent sensors and the high-speed camera of the aerial vision monitoring device based on the wireless network. Step 2: The high-speed camera and the vibration sensor array transmit the collected image data and vibration data to the blasting vibration analysis module in real time through the wireless network. Step 3: Initiate the blasting. The blasting vibration analysis module analyzes the image data based on the image feature recognition algorithm and extracts the blasting-related visual feature change data based on the time sequence. The blasting vibration analysis module analyzes the vibration data and respectively collects the vibration change data corresponding to multiple blasting vibration monitoring intelligent sensors based on the synchronous time sequence of the image data. Step 4: Based on the blasting-related visual feature change data extracted in Step 3, the blasting vibration analysis module uses image processing software to draw a feature point matching diagram and outputs a schematic diagram of the associated visual feature changes. Step 5: The blasting vibration analysis module performs a time series analysis based on the vibration change data extracted in Step 3, extracts the time domain and frequency domain characteristics of the vibration signal, uses a data visualization tool to draw a vibration data time series diagram, and superimposes the vibration data time series diagram onto the schematic diagram of the associated visual feature changes to form a blasting vibration monitoring schematic diagram.

[0005] By adopting the above technical solution, through the combination of an aerial vision monitoring device and a ground vibration sensor array, a full-range monitoring of the blasting process can be achieved. It can not only capture the ground vibration data but also observe the flying situation of the fragments generated by the explosion. All the blasting vibration monitoring intelligent sensors and the high-speed cameras of the aerial vision monitoring device are time-synchronized, ensuring the consistency of the image data and the vibration data, which is crucial for subsequent data analysis and event reconstruction.

[0006] The use of a wireless network enables the real-time transmission of image data and vibration data to the analysis module, improving the timeliness of monitoring and allowing on-site personnel to make decisions in a timely manner.

[0007] By using an image feature recognition algorithm to analyze the images captured by the high-speed cameras, the visual feature changes associated with the blasting can be accurately extracted, providing intuitive evidence for understanding the explosion effect.

[0008] Through image processing software and data visualization tools, complex vibration data and visual feature changes can be converted into easy-to-understand charts and schematic diagrams, facilitating non-professionals to quickly grasp the key information.

[0009] The generation of the blasting vibration monitoring schematic diagram helps to evaluate the safety of the blasting operation and identify possible safety risks, such as the flying range of fragments and the vibration influence area.

[0010] By analyzing the vibration data and visual feature changes, the blasting design can be optimized, for example, adjusting the amount of explosive, the location of the blasting point, or the safety distance, to reduce the impact on the surrounding environment.

[0011] If an accident occurs during the blasting process, the synchronized visual and vibration data can help accident investigators reconstruct the accident process, find out the causes, and formulate preventive measures.

[0012] The application of wireless communication technology enables the remote conduct of blasting monitoring, which is particularly beneficial for dangerous or inaccessible blasting sites.

[0013] By integrating advanced data acquisition, synchronization, transmission, and analysis technologies, it provides an efficient, accurate, and safe monitoring tool for blasting operations, which helps improve the overall level of blasting operations.

[0014] Optionally, in step 1, an NTP server is set up in the wireless network. The NTP server obtains accurate time from a GPS clock. All the blasting vibration monitoring intelligent sensors of the high-speed cameras and vibration sensor arrays of the aerial vision monitoring device are connected to the NTP server through the wireless network, and query the NTP server time for time synchronization before the blasting occurs.

[0015] By adopting the above technical solution, achieving time synchronization is a key step to ensure the consistency of the vibration sensor data and the camera data of the aerial vision monitoring device. NTP is a widely used protocol for synchronizing the time of computer clocks in a computer network. An NTP server is set up in the wireless network, and the NTP server obtains accurate time from one or more reliable time sources (such as atomic clocks or GPS clocks). All the blasting vibration monitoring intelligent sensors and the high-speed cameras of the aerial vision monitoring device are connected to the NTP server through the wireless network for time synchronization at the start of monitoring, and the NTP server time can also be set to be queried and synchronized regularly (for example, every minute) during the blasting preparation process.

[0016] Optionally, in step 3, the SIFT algorithm is used to extract the blasting-related visual features and position coordinates in each frame of the image before and after the blasting. The blasting-related visual features are the visual features of fragments with a diameter greater than 0.5 cm.

[0017] By adopting the above technical solution, the SIFT algorithm can extract feature points with scale invariance in the image, which means that even if the fragments change in size, angle, or illumination during the blasting process, the algorithm can still stably identify and track these features. The SIFT algorithm can provide the accurate position coordinates of the feature points, which is crucial for analyzing the trajectory and speed of the fragment scattering. By matching the feature points in the images before and after the blasting, the movement trajectory of the fragments with a diameter greater than 0.5 cm during the explosion can be effectively tracked, so as to evaluate their potential lethality.

[0018] Fragments smaller than 0.5 cm are difficult to track visually and have less lethality.

[0019] Identifying and tracking fragments with lethality helps evaluate the safety risks of blasting operations and provides a scientific basis for formulating safety measures.

[0020] Optionally, the feature point description formula of the blasting-related visual features is: ; Wherein, It is a function used to calculate the feature point descriptor in the SIFT algorithm. x is the position coordinate of the fragment feature point. is the motion direction of the fragment feature point. is the scale of the fragment feature point. is the Difference of Gaussians function. i is the different fragment scale levels, and n is the number of layers in the scale space.

[0021] By adopting the above technical solution, the Difference of Gaussians function is used to detect the extreme points in the scale space. The motion direction of the fragment feature point is determined by calculating the gradient direction of the local image area. The scale of the fragment feature point is related to the standard deviation of the Gaussian kernel in the scale space where the feature point is located.

[0022] Optionally, in step 4, the movement trajectory of the feature point is represented by color coding or connection lines, and the output change diagram is in PNG or JPEG format.

[0023] By adopting the above technical solution, the color coding and connection lines provide an intuitive movement trajectory of the feature points, enabling analysts to quickly understand and analyze the dynamic behavior of the fragments or feature points. Distinguishing different feature points or fragments by different colors or line types helps to clearly display multiple trajectories, avoid confusion, and facilitate communication; the images in PNG or JPEG format are easy to share and embed in reports, facilitating the communication of analysis results within the team or with other stakeholders.

[0024] Optionally, in step 3, the shooting time points of each frame of image before and after the explosion are parsed, the vibration data of multiple blasting vibration monitoring intelligent sensors are parsed respectively, and multiple groups of vibration value data corresponding to the shooting time points of each frame of image are extracted respectively.

[0025] By adopting the above technical solution, the frame rate of the high-speed camera can reach 1000 frames per second or even higher. If a frame rate of 1000 frames per second is adopted, it means that one frame of image can be generated in 1 millisecond, which can better monitor the dynamic picture during the instantaneous explosion process. The vibration data of the blasting vibration monitoring intelligent sensors can be linear, and the vibration data is processed corresponding to the shooting time points of each frame of image, providing data support for the data synchronization of the subsequent blasting vibration monitoring schematic diagram.

[0026] Optionally, in step 5, the visualization radiation lines are generated according to the radiation lines arranged by the vibration sensor array. The geometric centers of each blasting vibration monitoring intelligent sensor are mapped to the corresponding positions of the visualization radiation lines to form multiple data nodes. Data display frames are set at each data node, and then the vibration data based on time series extracted in step 3 is mapped to multiple data display frames to form a vibration data time series diagram.

[0027] By adopting the above technical solution, through radiation visualization, the spatial relationship between the vibration sensor array and the blasting point can be intuitively displayed, helping analysts understand the impact of sensor layout on data acquisition. Mapping the geometric center of each sensor onto the visualized radiation lines ensures a one-to-one correspondence between the vibration data and the actual sensor positions, improving the accuracy of data analysis. Combining the visual feature changes and the vibration data time series diagram provides multi-dimensional data analysis, which helps to comprehensively understand the impact of the blasting process. By presenting the data of all sensors within the same visual framework, the comparison between the vibration data captured by different sensors becomes simple and fast. The data display box can update the vibration data in real time, enabling the monitoring personnel to track the vibration changes during the blasting process in real time. Mapping the vibration data directly onto the graphical interface reduces the time for data analysis and improves the efficiency of data interpretation. By observing the vibration data of sensors at different positions, the impact of blasting on different areas can be evaluated, providing a basis for risk assessment.

[0028] Optionally, the vibration data is triaxial vibration velocity and vibration frequency.

[0029] A blasting vibration monitoring system based on vision and vibration sensors is used to implement the blasting vibration monitoring method based on vision and vibration sensors. The blasting vibration monitoring system includes an aerial vision monitoring device, a vibration sensor array, a blasting vibration analysis module, and an NTP server. The aerial vision monitoring device includes a drone and a high-speed camera. The drone flies at a set height directly above the blasting point. The high-speed camera is mounted on the bottom mission payload platform of the drone, with the lens facing downwards directly towards the blasting point. The high-speed camera is communicatively connected to the blasting vibration analysis module and the NTP server respectively through a wireless communication network. The vibration sensor array includes multiple vibration monitoring mounting plates and multiple blasting vibration monitoring intelligent sensors. The multiple vibration monitoring mounting plates are radially placed around the blasting point respectively. The multiple blasting vibration monitoring intelligent sensors are respectively installed on the upper surfaces of the multiple vibration monitoring mounting plates and are communicatively connected to the blasting vibration analysis module and the NTP server respectively through a wireless communication network. The blasting vibration analysis module includes a wireless communication module and an analysis computer. The analysis computer is wirelessly communicatively connected to the high-speed camera and the multiple blasting vibration monitoring intelligent sensors respectively through the wireless communication module, and monitors the blasting vibration process based on the image data collected by the high-speed camera and the vibration data collected by the vibration sensor array.

[0030] Optionally, taking the geometric center of the blasting point as the origin, using the eight direction lines of true east, southeast, south, southwest, true west, northwest, north, and northeast from the origin as the radiation lines, eight blasting vibration monitoring intelligent sensors are respectively arranged on the eight radiation lines more than two meters in diameter away from the origin of the blasting point. Thereafter, eight blasting vibration monitoring intelligent sensors are arranged every five meters, and the farthest blasting vibration monitoring intelligent sensor is 102 meters away from the origin.

[0031] By adopting the above technical solution, a radial blasting monitoring layout in eight directions can be used to more comprehensively understand the impact of blasting on the surrounding area.

[0032] In summary, the present invention includes at least one of the following beneficial technical effects: By combining an aerial vision monitoring device and a ground vibration sensor array to achieve all-round monitoring of the blasting process, not only can ground vibration data be captured, but also the scattering of debris generated by the explosion can be observed. All blasting vibration monitoring intelligent sensors and the high-speed cameras of the aerial vision monitoring device are time-synchronized to ensure the consistency of image data and vibration data, which is crucial for subsequent data analysis and event reconstruction.

[0033] By using an image feature recognition algorithm to analyze the images captured by the high-speed camera, the visual feature changes associated with blasting can be accurately extracted, providing intuitive evidence for understanding the explosion effect.

[0034] Through image processing software and data visualization tools, complex vibration data and visual feature changes can be converted into easy-to-understand charts and schematic diagrams, facilitating non-professionals to quickly grasp key information.

[0035] The generation of the schematic diagram of blasting vibration monitoring helps to evaluate the safety of blasting operations and identify possible safety risks, such as the scattering range of debris, the vibration influence area, etc.

[0036] By analyzing the vibration data and visual feature changes, the blasting design can be optimized, for example, adjusting the amount of explosive, the location of the blasting point or the safety distance, to reduce the impact on the surrounding environment.

[0037] If an accident occurs during the blasting process, the synchronized visual and vibration data can help accident investigators reproduce the accident process, find out the reasons, and formulate preventive measures. Brief Description of the Drawings

[0038] Figure 1 is a schematic flow diagram of the blasting vibration monitoring method based on vision and vibration sensors of the present invention; Figure 2 is a schematic diagram of the electrical component connection principle of the blasting vibration monitoring device based on vision and vibration sensors of the present invention; Figure 3 is a schematic top view of the vibration sensor array arrangement of the blasting vibration monitoring device based on vision and vibration sensors of the present invention; Description of reference numerals: 1. Aerial vision monitoring device; 11. High-speed camera; 12. UAV; 2. Vibration sensor array; 21. Intelligent blasting vibration monitoring sensor; 22. Vibration monitoring mounting plate; 3. Blasting vibration analysis module; 31. Wireless communication module; 32. Analysis computer; 4. NTP server. Detailed implementation mode

[0039] The present invention will be further described in detail below with reference to the accompanying drawings.

[0040] The embodiment of the present invention discloses a blasting vibration monitoring method and system based on vision and vibration sensors.

[0041] Refer to Figures 1-3 , Embodiment 1, a blasting vibration monitoring method based on vision and vibration sensors. An aerial vision monitoring device 1 is arranged at a set height directly above the blasting point 100, and a vibration sensor array 2 is arranged radially around the blasting point 100. The vision monitoring device 1 and the vibration sensor array 2 are wirelessly communicatively connected to a computer-based blasting vibration analysis module 3. The method for monitoring the blasting vibration process includes the following steps: Step 1, start all the intelligent blasting vibration monitoring sensors 21 of the vibration sensor array 2, start the high-speed camera 11 of the aerial vision monitoring device 1, and perform time synchronization on all the intelligent blasting vibration monitoring sensors 21 and the high-speed camera 11 of the aerial vision monitoring device 1 based on the wireless network; Step 2, the high-speed camera 11 and the vibration sensor array 2 transmit the collected image data and vibration data to the blasting vibration analysis module 3 in real time through the wireless network; Step 3, start the blasting. The blasting vibration analysis module 3 analyzes the image data based on the image feature recognition algorithm, and extracts the blasting-related visual feature change data based on the time sequence; the blasting vibration analysis module 3 analyzes the vibration data, and respectively collects the vibration change data corresponding to multiple intelligent blasting vibration monitoring sensors 21 based on the synchronous time sequence of the image data; Step 4, the blasting vibration analysis module 3 draws a feature point matching diagram by using image processing software based on the blasting-related visual feature change data extracted in Step 3, and outputs a schematic diagram of the associated visual feature change; Step 5, the blasting vibration analysis module 3 performs time sequence analysis on the vibration change data extracted in Step 3, extracts the time domain and frequency domain features of the vibration signal, uses a data visualization tool to draw a vibration data time sequence diagram, and superimposes the vibration data time sequence diagram on the schematic diagram of the associated visual feature change to form a blasting vibration monitoring schematic diagram.

[0042] By combining the aerial vision monitoring device 1 and the ground vibration sensor array 2, it is possible to achieve all-round monitoring of the blasting process, not only capturing ground vibration data but also observing the scattering of debris generated by the explosion. All the blasting vibration monitoring intelligent sensors 21 and the high-speed cameras 11 of the aerial vision monitoring device 1 are time-synchronized, ensuring the consistency of image data and vibration data, which is crucial for subsequent data analysis and event reconstruction.

[0043] The use of a wireless network enables the real-time transmission of image data and vibration data to the analysis module, improving the timeliness of monitoring and allowing on-site personnel to make decisions promptly.

[0044] By analyzing the images captured by the high-speed cameras 11 using image feature recognition algorithms, the visual feature changes associated with blasting can be accurately extracted, providing intuitive evidence for understanding the explosion effect.

[0045] Through image processing software and data visualization tools, complex vibration data and visual feature changes can be transformed into easy-to-understand charts and schematic diagrams, facilitating non-professionals to quickly grasp key information.

[0046] The generation of a schematic diagram of blasting vibration monitoring helps to evaluate the safety of blasting operations and identify possible safety risks, such as the range of debris scattering and the vibration impact area.

[0047] By analyzing vibration data and visual feature changes, the blasting design can be optimized, for example, adjusting the amount of explosive, the location of the blasting point, or the safety distance, to reduce the impact on the surrounding environment.

[0048] If an accident occurs during the blasting process, the synchronized visual and vibration data can help accident investigators reconstruct the accident process, identify the causes, and formulate preventive measures.

[0049] The application of wireless communication technology enables remote blasting monitoring, which is particularly beneficial for dangerous or inaccessible blasting sites.

[0050] By integrating advanced data acquisition, synchronization, transmission, and analysis technologies, an efficient, accurate, and safe monitoring tool is provided for blasting operations, helping to improve the overall level of blasting operations.

[0051] In Example 2, in step 1, an NTP server 4 is set up in the wireless network. The NTP server 4 obtains accurate time from the GPS clock. The high-speed cameras 11 of the aerial vision monitoring device 1 and all the blasting vibration monitoring intelligent sensors 21 of the vibration sensor array 2 are connected to the NTP server 4 through the wireless network and query the time of the NTP server 4 for time synchronization before the blasting occurs.

[0052] Implementing time synchronization is a crucial step in ensuring the consistency of vibration sensor data and the camera data of the aerial vision monitoring device. NTP is a widely used protocol for synchronizing the time of computer clocks in a computer network. An NTP server 4 is set up in the wireless network, and this NTP server obtains accurate time from one or more reliable time sources (such as atomic clocks or GPS clocks). All the high-speed cameras 11 of the blasting vibration monitoring intelligent sensors 21 and the aerial vision monitoring device 1 are connected to the NTP server through the wireless network to perform time synchronization at the start of monitoring. During the blasting preparation process, it is also possible to set up regular (e.g., every minute) queries to synchronize with the time of the NTP server 4.

[0053] In Embodiment 3, in step 3, the SIFT algorithm is used to extract the blasting-related visual features and position coordinates in each frame of the image before and after blasting. The blasting-related visual features are the visual features of fragments with a diameter greater than 0.5 cm.

[0054] The SIFT algorithm can extract feature points with scale invariance in the image, which means that even if the fragments change in size, angle, or illumination during the blasting process, the algorithm can still stably identify and track these features. The SIFT algorithm can provide the accurate position coordinates of the feature points, which is crucial for analyzing the trajectory and speed of the fragment scattering. By matching the feature points in the images before and after blasting, the movement trajectory of fragments with a diameter greater than 0.5 cm during the explosion can be effectively traced, thereby evaluating their potential lethality.

[0055] Fragments smaller than 0.5 cm are difficult to track visually and have less lethality.

[0056] Identifying and tracking lethal fragments helps to evaluate the safety risks of blasting operations and provides a scientific basis for formulating safety measures.

[0057] In Embodiment 4, the feature point description formula for the blasting-related visual features is: ; where is the function used to calculate the feature point descriptor in the SIFT algorithm, x is the position coordinate of the fragment feature point, is the movement direction of the fragment feature point, is the scale of the fragment feature point, is the difference-of-Gaussians function, i is the different fragment scale levels, and n is the number of layers in the scale space.

[0058] The difference-of-Gaussians function is used to detect the extreme points in the scale space. The movement direction It is determined by calculating the gradient direction of the local image region. The scale of the fragment feature point is related to the standard deviation of the Gaussian kernel in the scale space where the feature point is located.

[0059] In Example 5, in step 4, the movement trajectory of the feature point is represented by color coding or connection lines, and the output change diagram is in PNG or JPEG format.

[0060] The color coding and connection line method provide an intuitive movement trajectory of the feature point, enabling analysts to quickly understand and analyze the dynamic behavior of the fragments or feature points. Different colors or line types are used to distinguish different feature points or fragments, which helps to clearly display multiple trajectories, avoid confusion, and facilitate communication; images in PNG or JPEG format are easy to share and embed in reports, facilitating the communication of analysis results within the team or with other stakeholders.

[0061] In Example 6, in step 3, the shooting time points of each frame of image before and after the explosion are parsed, the vibration data of multiple blasting vibration monitoring intelligent sensors 21 are respectively parsed, and multiple groups of vibration value data corresponding to the shooting time points of each frame of image are respectively extracted.

[0062] The frame rate of the high-speed camera 11 can be selected up to 1000 frames per second, or even higher. If a frame rate of 1000 frames per second is adopted, it means that one frame of image can be generated in 1 millisecond, which can better monitor the dynamic picture during the instantaneous explosion process. The vibration data of the blasting vibration monitoring intelligent sensor 21 can be linear, and the vibration data is processed corresponding to the shooting time point of each frame of image, providing data support for the data synchronization of the subsequent blasting vibration monitoring schematic diagram.

[0063] In Example 7, in step 5, visualization radiation lines are generated according to the radiation lines arranged by the vibration sensor array 2, and the geometric centers of each blasting vibration monitoring intelligent sensor 21 are mapped to the corresponding positions of the visualization radiation lines to form multiple data nodes. Data display frames are set at each data node, and then the vibration data based on time series extracted in step 3 is mapped to multiple data display frames to form a vibration data time series diagram.

[0064] Through radiation visualization, the spatial relationship between the vibration sensor array and the blasting point can be intuitively displayed, helping analysts understand the impact of sensor layout on data acquisition. Mapping the geometric center of each sensor to the visualized radiation lines ensures a one-to-one correspondence between the vibration data and the actual sensor positions, improving the accuracy of data analysis. Combining visual feature changes and the vibration data time series diagram provides multi-dimensional data analysis, which helps to comprehensively understand the impact of the blasting process. By presenting the data of all sensors within the same visual framework, the comparison between the vibration data captured by different sensors becomes simple and fast. The data display box can update the vibration data in real time, enabling the monitoring personnel to track the vibration changes during the blasting process in real time. Mapping the vibration data directly onto the graphical interface reduces the time for data analysis and improves the efficiency of data interpretation. By observing the vibration data of sensors at different positions, the impact of blasting on different areas can be evaluated, providing a basis for risk assessment.

[0065] Example 8, the vibration data is three-axis vibration velocity and vibration frequency.

[0066] Example 9, a blasting vibration monitoring system based on vision and vibration sensors is used to implement the blasting vibration monitoring method based on vision and vibration sensors. The blasting vibration monitoring system includes an aerial vision monitoring device 1, a vibration sensor array 2, a blasting vibration analysis module 3, and an NTP server 4. The aerial vision monitoring device 1 includes a drone 12 and a high-speed camera 11. The drone 12 flies at a set height directly above the blasting point 100. The high-speed camera 11 is mounted on the bottom payload platform of the drone 12, with the lens facing downwards directly towards the blasting point 100. The high-speed camera 11 is communicatively connected to the blasting vibration analysis module 3 and the NTP server 4 respectively through a wireless communication network. The vibration sensor array 2 includes a plurality of vibration monitoring mounting plates 22 and a plurality of blasting vibration monitoring intelligent sensors 21. The plurality of vibration monitoring mounting plates 22 are radially placed around the blasting point 100 respectively. The plurality of blasting vibration monitoring intelligent sensors 21 are respectively mounted on the upper surfaces of the plurality of vibration monitoring mounting plates 22 and are communicatively connected to the blasting vibration analysis module 3 and the NTP server 4 respectively through a wireless communication network. The blasting vibration analysis module 3 includes a wireless communication module 31 and an analysis computer 32. The analysis computer 32 is wirelessly communicatively connected to the high-speed camera 11 and the plurality of blasting vibration monitoring intelligent sensors 21 respectively through the wireless communication module 31. The blasting vibration process is monitored based on the image data collected by the high-speed camera 11 and the vibration data collected by the vibration sensor array 2.

[0067] Example 10: Taking the geometric center of the blasting point 100 as the origin, using the eight direction lines of due east, southeast, due south, southwest, due west, northwest, due north, and northeast from the origin as the radiation lines, eight blasting vibration monitoring intelligent sensors 21 are respectively arranged on the eight radiation lines more than two meters in diameter away from the origin of the blasting point 100. Then, eight blasting vibration monitoring intelligent sensors 21 are arranged every five meters hereafter, and the farthest blasting vibration monitoring intelligent sensor 21 is 102 meters away from the origin.

[0068] Adopting a radial blasting monitoring layout in eight directions can more comprehensively understand the impact of blasting on the surrounding area.

[0069] Specific example: A certain city is carrying out an infrastructure construction project, which involves rock blasting operations. To ensure the safety and effectiveness of the blasting operations, the project team decides to use a blasting vibration monitoring system based on vision and vibration sensors to monitor the blasting process.

[0070] At a position 50 meters directly above the blasting point 100, the project team deploys a drone 12 equipped with a high-speed camera 11, ensuring that the camera lens faces downward directly towards the blasting point 100.

[0071] Around the blasting point 100, a vibration sensor array 2 is arranged radially along eight direction lines (due east, southeast, due south, southwest, due west, northwest, due north, and northeast). One blasting vibration monitoring intelligent sensor 21 is placed every five meters on each direction line, and the farthest distance from the blasting point is 102 meters.

[0072] Through the wireless network, all blasting vibration monitoring intelligent sensors 21 and the high-speed camera 11 are connected to the NTP server 4 for time synchronization, ensuring that the time deviation of all devices is within 1 millisecond.

[0073] Before blasting, start the high-speed camera 11 and all blasting vibration monitoring intelligent sensors 21 to start collecting image data and vibration data.

[0074] The high-speed camera 11 records the blasting process at a frame rate of 1000 frames per second, and the vibration sensor 21 records vibration data at a sampling rate of 100 Hz.

[0075] The collected data is transmitted to the blasting vibration analysis module 3 in real time through the wireless network.

[0076] Blasting is executed, and at the same time, the high-speed camera 11 and the vibration sensor 21 continue to record data.

[0077] The blasting vibration analysis module 3 uses the SIFT algorithm to process the image data collected by the high-speed camera 11, and extracts the visual features and position coordinates of the fragments with a diameter greater than 0.5 cm.

[0078] The blasting vibration analysis module 3 performs a timing analysis on the vibration data collected by the vibration sensors 21 to extract the changes in vibration velocity and frequency of each sensor before and after blasting.

[0079] Based on the extracted visual feature data, the blasting vibration analysis module 3 uses image processing software to draw a feature point matching diagram and outputs a schematic diagram showing the associated visual feature changes.

[0080] According to the timing analysis results, the blasting vibration analysis module 3 draws a timing diagram of the vibration data and sets data display frames at the positions of each vibration sensor 21.

[0081] The timing diagram of the vibration data is superimposed on the schematic diagram showing the associated visual feature changes to form a schematic diagram for blasting vibration monitoring.

[0082] The monitoring schematic diagram shows that the fragments generated by the blasting mainly scatter in the southeast direction, and the maximum flight distance is about 80 meters.

[0083] The timing diagram of the vibration data shows that the ground vibration caused by the blasting is the strongest in the southeast direction, but the vibrations at all monitoring points are within the safety threshold.

[0084] The project team adjusted the subsequent blasting plan according to the monitoring results, increased the buffer zone in the southeast direction, and appropriately reduced the amount of explosive used.

[0085] The project team successfully utilized the blasting vibration monitoring system based on vision and vibration sensors to improve the safety and efficiency of blasting operations.

[0086] The above are all preferred embodiments of the present invention, and do not limit the protection scope of the present invention. Therefore, all equivalent changes made according to the structure, shape, and principle of the present invention should be covered within the protection scope of the present invention.

Claims

1. A blasting vibration monitoring method based on vision and vibration sensors, characterized in that: An aerial vision monitoring device (1) is arranged at a set height directly above the blasting point (100), and a vibration sensor array (2) is arranged radially around the blasting point (100). The vision monitoring device (1) and the vibration sensor array (2) are wirelessly communicatively connected to a computer-based blasting vibration analysis module (3). The method for monitoring the blasting vibration process includes the following steps: Step 1, start all the blasting vibration monitoring intelligent sensors (21) of the vibration sensor array (2), start the high-speed camera (11) of the aerial vision monitoring device (1), and perform time synchronization on all the blasting vibration monitoring intelligent sensors (21) and the high-speed camera (11) of the aerial vision monitoring device (1) based on the wireless network; Step 2, the high-speed camera (11) and the vibration sensor array (2) transmit the collected image data and vibration data to the blasting vibration analysis module (3) in real time through the wireless network; Step 3, initiate the blasting. The blasting vibration analysis module (3) analyzes the image data based on the image feature recognition algorithm and extracts the blasting-related visual feature change data based on the time sequence; the blasting vibration analysis module (3) analyzes the vibration data and respectively collects the vibration change data corresponding to multiple blasting vibration monitoring intelligent sensors (21) based on the synchronous time sequence of the image data; Step 4, the blasting vibration analysis module (3) draws a feature point matching diagram by using image processing software based on the blasting-related visual feature change data extracted in Step 3 and outputs a schematic diagram of the associated visual feature change; Step 5, the blasting vibration analysis module (3) performs time sequence analysis based on the vibration change data extracted in Step 3, extracts the time domain and frequency domain features of the vibration signal, uses a data visualization tool to draw a vibration data time sequence diagram, and superimposes the vibration data time sequence diagram on the schematic diagram of the associated visual feature change to form a blasting vibration monitoring schematic diagram.

2. The blasting vibration monitoring method based on vision and vibration sensors according to claim 1, wherein: In Step 1, an NTP server (4) is set in the wireless network. The NTP server (4) obtains the accurate time from the GPS clock. The high-speed camera (11) of the aerial vision monitoring device (1) and all the blasting vibration monitoring intelligent sensors (21) of the vibration sensor array (2) are connected to the NTP server (4) through the wireless network, and query the time of the NTP server (4) for time synchronization before the blasting occurs.

3. The blasting vibration monitoring method based on vision and vibration sensors according to claim 1, wherein: In Step 3, the SIFT algorithm is used to extract the blasting-related visual features and position coordinates in each frame of image before and after the blasting. The blasting-related visual features are the visual features of fragments with a diameter greater than 0.5 cm.

4. The blasting vibration monitoring method based on vision and vibration sensors according to claim 3, characterized in that: The feature point description formula of the blasting-related visual features is: ； Among them, is a function used to calculate the feature point descriptor in the SIFT algorithm. x is the position coordinate of the fragment feature point, is the motion direction of the fragment feature point, is the scale of the fragment feature point, is the Difference of Gaussians function. i is the different fragment scale levels, and n is the number of layers in the scale space.

5. The blasting vibration monitoring method based on vision and vibration sensors according to claim 4, characterized in that: In Step 4, the movement trajectory of the feature points is represented by color coding or connection method, and the output change diagram is in PNG or JPEG format.

6. The blasting vibration monitoring method based on vision and vibration sensors according to claim 5, characterized in that: In Step 3, the shooting time points of each frame of image before and after the blasting are analyzed, the vibration data of multiple blasting vibration monitoring intelligent sensors (21) are respectively analyzed, and multiple groups of vibration value data corresponding to each frame of image shooting time point are respectively extracted.

7. The blasting vibration monitoring method based on vision and vibration sensors according to claim 6, characterized in that: In step 5, visualization radiation lines are generated according to the arrangement of the vibration sensor array (2). The geometric centers of each blasting vibration monitoring intelligent sensor (21) are mapped to corresponding positions on the visualization radiation lines to form a plurality of data nodes. Data display frames are set at each data node, and then the vibration data based on time series extracted in step 3 is mapped to the plurality of data display frames to form a vibration data time series diagram.

8. The blasting vibration monitoring method based on vision and vibration sensors according to claim 7, characterized in that: The vibration data is triaxial vibration velocity and vibration frequency.

9. Blasting vibration monitoring system based on vision and vibration sensors, characterized in that: For implementing the blasting vibration monitoring method based on vision and vibration sensors according to any one of claims 1-8, the blasting vibration monitoring system includes an aerial vision monitoring device (1), a vibration sensor array (2), a blasting vibration analysis module (3), and an NTP server (4). The aerial vision monitoring device (1) includes a drone (12) and a high-speed camera (11). The drone (12) flies at a set height directly above the blasting point (100). The high-speed camera (11) is mounted on the bottom mission payload platform of the drone (12) with the lens facing downwards directly towards the blasting point (100). The high-speed camera (11) is communicatively connected to the blasting vibration analysis module (3) and the NTP server (4) respectively through a wireless communication network. The vibration sensor array (2) includes a plurality of vibration monitoring mounting plates (22) and a plurality of blasting vibration monitoring intelligent sensors (21). The plurality of vibration monitoring mounting plates (22) are radially placed around the blasting point (100). The plurality of blasting vibration monitoring intelligent sensors (21) are respectively mounted on the upper surfaces of the plurality of vibration monitoring mounting plates (22) and are communicatively connected to the blasting vibration analysis module (3) and the NTP server (4) respectively through a wireless communication network. The blasting vibration analysis module (3) includes a wireless communication module (31) and an analysis computer (32). The analysis computer (32) is wirelessly communicatively connected to the high-speed camera (11) and the plurality of blasting vibration monitoring intelligent sensors (21) respectively through the wireless communication module (31), and monitors the blasting vibration process based on the image data collected by the high-speed camera (11) and the vibration data collected by the vibration sensor array (2).

10. The blasting vibration monitoring system based on vision and vibration sensors according to claim 9, characterized in that: Taking the geometric center of the blasting point (100) as the origin, eight radiation lines in the directions of due east, southeast, due south, southwest, due west, northwest, due north, and northeast of the origin are used as the radiation lines. Eight blasting vibration monitoring intelligent sensors (21) are respectively arranged on the eight radiation lines more than two meters in diameter away from the origin of the blasting point (100). Thereafter, eight blasting vibration monitoring intelligent sensors (21) are arranged every five meters. The farthest blasting vibration monitoring intelligent sensor (21) is 102 meters away from the origin.

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