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

Abstract

The present invention discloses a blasting vibration monitoring method and system based on visual and vibration sensors, which relates to the technical field of blasting vibration monitoring. An aerial visual monitoring device is arranged at a height set just above the blasting point, and a vibration sensor array is radially arranged around the blasting point. The visual monitoring device and the vibration sensor array are wirelessly connected to a computer-based blasting vibration analysis module. The present invention realizes all-round monitoring of the blasting process by combining an aerial visual monitoring device and a ground vibration sensor array. It can not only capture ground vibration data, but also observe the scattering of fragments produced by the explosion. The images captured by the high-speed camera are analyzed using an image feature recognition algorithm, providing intuitive evidence for understanding the explosion effect. Through image processing software and data visualization tools, complex vibration data and visual feature changes can be converted into easy-to-understand charts and diagrams, so that non-professionals can also quickly grasp key information.

Description

Technical Field

[0001] The present invention relates to the technical field of blasting vibration monitoring, and in particular 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. Existing technologies mainly include the following directions:

[0003] Seismograph monitoring: Measure the seismic waves generated by blasting with a seismograph and analyze parameters such as vibration intensity and frequency. Accelerometer monitoring: Install accelerometers on buildings or the ground to collect real-time blasting vibration data. Microseismic monitoring: Utilize highly sensitive sensors to monitor changes in microseismic signals during blasting.

[0004] The technical defects of the above-mentioned traditional blasting vibration monitoring technology are:

[0005] Seismographs and accelerometers have a small monitoring range and cannot cover a large area. They are also difficult to reflect the overall vibration conditions around the blasting point. During the blasting process, vibration monitoring alone is not enough. For some blasting-related features, such as gravel, if they are not monitored, it is difficult to understand the trajectory and speed of high-speed gravel produced by the blasting, and the additional destructiveness caused by the blasting cannot be controlled. Summary of the Invention

[0006] In order 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:

[0007] The blasting vibration monitoring method based on visual and vibration sensors includes: an aerial visual monitoring device is arranged at a height directly above the blasting point; a vibration sensor array is radially arranged around the blasting point; the visual monitoring device and the vibration sensor array are wirelessly connected to a computer-based blasting vibration analysis module; and the blasting vibration process monitoring method includes the following steps:

[0008] Step 1: Start all blasting vibration monitoring smart sensors of the vibration sensor array, start the high-speed camera of the aerial visual monitoring device, and synchronize the time of all blasting vibration monitoring smart sensors and the high-speed camera of the aerial visual monitoring device based on the wireless network;

[0009] Step 2: The high-speed camera and vibration sensor array transmit the collected image data and vibration data to the blasting vibration analysis module in real time via a wireless network;

[0010] Step 3: Start 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 collects the vibration change data corresponding to multiple blasting vibration monitoring intelligent sensors based on the synchronous time sequence of the image data.

[0011] Step 4: The blasting vibration analysis module uses image processing software to draw a feature point matching graph based on the blasting-related visual feature change data extracted in step 3, and outputs a schematic diagram of the related visual feature changes;

[0012] In step 5, the blasting vibration analysis module performs time series analysis based on the vibration change data extracted in step 3, extracts the time domain and frequency domain features of the vibration signal, uses data visualization tools to draw a time series diagram of the vibration data, and superimposes the time series diagram of the vibration data onto the associated visual feature change diagram to form a blasting vibration monitoring diagram.

[0013] By employing this technical solution, combining aerial visual monitoring with an array of ground vibration sensors, a comprehensive monitoring system for the blasting process can be achieved. This not only captures ground vibration data but also allows observation of the fragmentation generated by the explosion. All intelligent blasting vibration monitoring sensors and the high-speed cameras in the aerial visual monitoring system are time-synchronized to ensure consistency between image and vibration data, which is crucial for subsequent data analysis and event reconstruction.

[0014] The use of wireless networks enables real-time transmission of image and vibration data to the analysis module, improving the timeliness of monitoring and allowing on-site personnel to make timely decisions.

[0015] By analyzing images captured by high-speed cameras using image feature recognition algorithms, we can accurately extract the visual feature changes associated with blasting, providing intuitive evidence for understanding the effects of explosions.

[0016] Image processing software and data visualization tools can transform complex vibration data and visual feature changes into easy-to-understand charts and diagrams, allowing non-professionals to quickly grasp key information.

[0017] The generation of blasting vibration monitoring diagrams helps to assess the safety of blasting operations and identify possible safety risks, such as the range of flying debris and the area affected by vibration.

[0018] By analyzing vibration data and visual feature changes, blasting design can be optimized, such as adjusting the amount of explosives, blasting point location, or safety distance to reduce the impact on the surrounding environment.

[0019] If an accident occurs during the blasting process, synchronized visual and vibration data can help accident investigators reconstruct the accident process, identify the cause, and develop preventive measures.

[0020] The application of wireless communication technology enables blasting monitoring to be carried out remotely, which is particularly beneficial for dangerous or inaccessible blasting sites.

[0021] By integrating advanced data acquisition, synchronization, transmission and analysis technologies, it provides an efficient, accurate and safe monitoring tool for blasting operations, helping to improve the overall level of blasting operations.

[0022] Optionally, in step 1, an NTP server is set up in the wireless network. The NTP server obtains accurate time from the GPS clock. The high-speed camera of the aerial visual monitoring device and all blasting vibration monitoring intelligent sensors of the vibration sensor array are connected to the NTP server through the wireless network. Before starting the blasting, the NTP server time is queried for time synchronization.

[0023] By adopting the above technical solution, achieving time synchronization is a key step in ensuring the consistency of vibration sensor data and camera data from the aerial visual monitoring system. NTP is a widely used protocol for synchronizing computer clocks in computer networks. An NTP server is set up in the wireless network. This NTP server obtains accurate time from one or more reliable time sources (such as atomic clocks or GPS clocks). All blasting vibration monitoring smart sensors and high-speed cameras in the aerial visual monitoring system are connected to the NTP server via the wireless network. Time synchronization is performed at the beginning of monitoring. During blasting preparation, the NTP server time can also be periodically queried (for example, every minute) to synchronize the time.

[0024] Optionally, in step 3, a SIFT algorithm is used to extract blast-related visual features and position coordinates in each frame of image before and after the blast. The blast-related visual features are visual features of fragments with a diameter greater than 0.5 cm.

[0025] By employing this technical solution, the SIFT algorithm can extract scale-invariant feature points from images. This means that even if the fragments change in size, angle, or lighting during the explosion, the algorithm can still reliably identify and track these features. The SIFT algorithm provides precise location coordinates of feature points, which is crucial for analyzing the trajectory and velocity of scattered debris. By matching feature points in pre- and post-blast images, the movement of fragments larger than 0.5 cm in diameter can be effectively tracked during the explosion, thereby assessing their potential lethality.

[0026] Fragments smaller than 0.5 cm are more difficult to track visually and are less lethal.

[0027] Identifying and tracking lethal fragments helps assess the safety risks of blasting operations and provides a scientific basis for formulating safety measures.

[0028] Optionally, the feature point description formula of the blast correlation visual feature is:

[0029] ;

[0030] in, It 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 direction of motion of the fragment feature points, is the scale of the fragment feature points, is the difference Gaussian function, i is the different fragment scale levels, and n is the number of levels in the scale space.

[0031] By adopting the above technical solution, The differential Gaussian function is used to detect the extreme points in the scale space and the movement direction of the fragment feature points 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.

[0032] Optionally, in step 4, the movement trajectory of the feature points is represented by color coding or connecting lines, and the output change map is in PNG or JPEG format.

[0033] By employing these technical solutions, color coding and line connections provide intuitive feature point movement trajectories, enabling analysts to quickly understand and analyze the dynamic behavior of fragments or feature points. Differentiating between feature points or fragments using different colors or line types helps clearly display multiple trajectories, avoids confusion, and facilitates communication. PNG or JPEG images are easy to share and embed in reports, facilitating communication of analysis results within the team or with other stakeholders.

[0034] Optionally, in step 3, the shooting time point of each frame image before and after the blasting is analyzed, the vibration data of multiple blasting vibration monitoring intelligent sensors are analyzed respectively, and multiple groups of vibration value data corresponding to the shooting time point of each frame image are extracted respectively.

[0035] 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 images during the instantaneous explosion process. The vibration data of the blasting vibration monitoring intelligent sensor can be linear, and the vibration data processing is performed corresponding to the shooting time point of each frame of the image, providing data support for the data synchronization of the subsequent blasting vibration monitoring diagram.

[0036] Optionally, in step 5, visual radial lines are generated according to the radial lines arranged in the vibration sensor array, and the geometric center of each blasting vibration monitoring intelligent sensor is mapped to the corresponding position of the visual radial line to form multiple data nodes. A data display frame is set at each data node, and the time-series-based vibration data extracted in step 3 is mapped to multiple data frames to form a vibration data time series diagram.

[0037] By implementing this technical solution, radial visualization can intuitively demonstrate the spatial relationship between the vibration sensor array and the blasting point, helping analysts understand the impact of sensor layout on data acquisition. Mapping the geometric center of each sensor onto the visualized radial lines ensures a one-to-one correspondence between vibration data and the actual sensor location, improving the accuracy of data analysis. Combining visual feature changes with vibration data time series graphs provides multi-dimensional data analysis, helping to fully understand the impact of the blasting process. By displaying data from all sensors within the same visual frame, comparison of vibration data captured by different sensors is simple and quick. The data display frame updates vibration data in real time, allowing monitors to track vibration changes during the blasting process in real time. Directly mapping vibration data to a graphical interface reduces data analysis time and improves data interpretation efficiency. By observing vibration data from sensors in different locations, the impact of blasting on different areas can be assessed, providing a basis for risk assessment.

[0038] Optionally, the vibration data is three-dimensional vibration speed and vibration frequency.

[0039] A blasting vibration monitoring system based on vision and vibration sensors is used to implement a blasting vibration monitoring method based on vision and vibration sensors. The blasting vibration monitoring system includes an aerial visual monitoring device, a vibration sensor array, a blasting vibration analysis module and an NTP server. The aerial visual monitoring device includes an unmanned aerial vehicle (UAV) and a high-speed camera. The UAV flies at a set altitude directly above the blasting point. The high-speed camera is mounted on the mission payload platform at the bottom of the UAV, with the lens facing downward toward the blasting point. The high-speed camera is respectively communicated with the blasting vibration analysis module and the NTP server via 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. The multiple blasting vibration monitoring intelligent sensors are respectively mounted on the upper surfaces of the multiple vibration monitoring mounting plates and are respectively communicated with the blasting vibration analysis module and the NTP server via a wireless communication network. The blasting vibration analysis module includes a wireless communication module and an analysis computer. The analysis computer is wirelessly connected to the high-speed camera and the multiple blasting vibration monitoring intelligent sensors via the wireless communication module. The blasting vibration process is monitored based on image data collected by the high-speed camera and vibration data collected by the vibration sensor array.

[0040] Optionally, with the geometric center of the blasting point as the origin and the eight direction lines of due east, southeast, due south, southwest, due west, northwest, due north and northeast of the origin as radial lines, eight blasting vibration monitoring intelligent sensors are arranged on the eight radial lines two meters in diameter from the blasting point origin, and then eight blasting vibration monitoring intelligent sensors are arranged every five meters. The farthest blasting vibration monitoring intelligent sensor is 102 meters away from the origin.

[0041] By adopting the above technical solution and a radial blasting monitoring layout in eight directions, we can have a more comprehensive understanding of the impact of blasting on the surrounding areas.

[0042] In summary, the present invention provides at least one of the following beneficial technical effects: By combining an aerial visual monitoring system with a ground vibration sensor array, comprehensive monitoring of the blasting process is achieved, capturing not only ground vibration data but also the dispersion of explosive debris. Time synchronization between all intelligent blasting vibration monitoring sensors and the high-speed cameras in the aerial visual monitoring system ensures consistency between image and vibration data, which is crucial for subsequent data analysis and event reconstruction.

[0043] By analyzing images captured by high-speed cameras using image feature recognition algorithms, we can accurately extract the visual feature changes associated with blasting, providing intuitive evidence for understanding the effects of explosions.

[0044] Image processing software and data visualization tools can transform complex vibration data and visual feature changes into easy-to-understand charts and diagrams, allowing non-professionals to quickly grasp key information.

[0045] The generation of blasting vibration monitoring diagrams helps to assess the safety of blasting operations and identify possible safety risks, such as the range of flying debris and the area affected by vibration.

[0046] By analyzing vibration data and visual feature changes, blasting design can be optimized, such as adjusting the amount of explosives, blasting point location, or safety distance to reduce the impact on the surrounding environment.

[0047] If an accident occurs during the blasting process, synchronized visual and vibration data can help accident investigators reconstruct the accident process, identify the cause, and develop preventive measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 Schematic diagram of the flow of the blasting vibration monitoring method based on vision and vibration sensors of the present invention;

[0049] Figure 2 This 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;

[0050] Figure 3 1. It is a top view schematic diagram of the arrangement of the vibration sensor array of the blasting vibration monitoring device based on vision and vibration sensors of the present invention;

[0051] Explanation of the accompanying symbols: 1. Aerial visual monitoring device; 11. High-speed camera; 12. UAV; 2. Vibration sensor array; 21. Blasting vibration monitoring intelligent sensor; 22. Vibration monitoring mounting plate; 3. Blasting vibration analysis module; 31. Wireless communication module; 32. Analysis computer; 4. NTP server. DETAILED DESCRIPTION

[0052] The present invention will be further described in detail below with reference to the accompanying drawings.

[0053] The embodiments of the present invention disclose a blasting vibration monitoring method and system based on vision and vibration sensors.

[0054] Reference Figure 1-Figure 3 In Example 1, a blasting vibration monitoring method based on visual and vibration sensors is provided. An aerial visual monitoring device 1 is arranged at a predetermined height directly above a blasting point 100. A vibration sensor array 2 is radially arranged around the blasting point 100. The visual monitoring device 1 and the vibration sensor array 2 are wirelessly connected to a computer-based blasting vibration analysis module 3. The blasting vibration process monitoring method includes the following steps:

[0055] Step 1: Start all blasting vibration monitoring smart sensors 21 of the vibration sensor array 2, start the high-speed camera 11 of the aerial visual monitoring device 1, and synchronize the time of all blasting vibration monitoring smart sensors 21 and the high-speed camera 11 of the aerial visual monitoring device 1 based on the wireless network;

[0056] 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 via a wireless network;

[0057] Step 3: Start 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 collects the vibration change data corresponding to the multiple blasting vibration monitoring intelligent sensors 21 based on the synchronous time sequence of the image data.

[0058] Step 4: The blasting vibration analysis module 3 uses image processing software to draw a feature point matching graph based on the blasting-related visual feature change data extracted in step 3, and outputs a schematic diagram of the related visual feature changes;

[0059] In step 5, the blasting vibration analysis module 3 performs time series 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 time series diagram of the vibration data, and superimposes the time series diagram of the vibration data onto the associated visual feature change diagram to form a blasting vibration monitoring diagram.

[0060] By combining the aerial visual monitoring system 1 with the ground vibration sensor array 2, a comprehensive monitoring of the blasting process can be achieved, capturing not only ground vibration data but also observing the dispersion of explosive debris. All blasting vibration monitoring intelligent sensors 21 and the high-speed camera 11 of the aerial visual monitoring system 1 are time-synchronized, ensuring consistency between image and vibration data, which is crucial for subsequent data analysis and event reconstruction.

[0061] The use of wireless networks enables real-time transmission of image and vibration data to the analysis module, improving the timeliness of monitoring and allowing on-site personnel to make timely decisions.

[0062] By analyzing the images captured by the high-speed camera 11 using an image feature recognition algorithm, the changes in visual features associated with the blast can be accurately extracted, providing intuitive evidence for understanding the effects of the blast.

[0063] Image processing software and data visualization tools can transform complex vibration data and visual feature changes into easy-to-understand charts and diagrams, allowing non-professionals to quickly grasp key information.

[0064] The generation of blasting vibration monitoring diagrams helps to assess the safety of blasting operations and identify possible safety risks, such as the range of flying debris and the area affected by vibration.

[0065] By analyzing vibration data and visual feature changes, blasting design can be optimized, such as adjusting the amount of explosives, blasting point location, or safety distance to reduce the impact on the surrounding environment.

[0066] If an accident occurs during the blasting process, synchronized visual and vibration data can help accident investigators reconstruct the accident process, identify the cause, and develop preventive measures.

[0067] The application of wireless communication technology enables blasting monitoring to be carried out remotely, which is particularly beneficial for dangerous or inaccessible blasting sites.

[0068] By integrating advanced data acquisition, synchronization, transmission and analysis technologies, it provides an efficient, accurate and safe monitoring tool for blasting operations, helping to improve the overall level of blasting operations.

[0069] 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 camera 11 of the aerial visual monitoring device 1 and all blasting vibration monitoring intelligent sensors 21 of the vibration sensor array 2 are connected to the NTP server 4 through the wireless network. Before the blasting is started, the time of the NTP server 4 is queried for time synchronization.

[0070] Time synchronization is a critical step in ensuring consistency between vibration sensor data and camera data from the aerial visual monitoring system. NTP is a widely used protocol for synchronizing computer clocks in computer networks. An NTP server 4 is set up in the wireless network. This NTP server obtains accurate time from one or more reliable time sources (such as atomic clocks or GPS clocks). All blasting vibration monitoring smart sensors 21 and the high-speed camera 11 of the aerial visual monitoring system 1 are connected to the NTP server via the wireless network. Time synchronization is performed at the start of monitoring. During blasting preparation, the time of the synchronized NTP server 4 can also be periodically queried (for example, every minute).

[0071] In Example 3, in step 3, the SIFT algorithm is used to extract blast-related visual features and position coordinates in each frame of image before and after the blast. The blast-related visual features are visual features of fragments with a diameter greater than 0.5 cm.

[0072] The SIFT algorithm extracts scale-invariant feature points from images. This means that even if fragments change in size, angle, or lighting during the explosion, the algorithm can still reliably identify and track these features. The SIFT algorithm provides precise location coordinates of feature points, which is crucial for analyzing the trajectory and velocity of scattered debris. By matching feature points in pre- and post-blast images, it is possible to effectively track the movement of fragments larger than 0.5 cm in diameter during the explosion, thereby assessing their potential lethality.

[0073] Fragments smaller than 0.5 cm are more difficult to track visually and are less lethal.

[0074] Identifying and tracking lethal fragments helps assess the safety risks of blasting operations and provides a scientific basis for formulating safety measures.

[0075] In Example 4, the feature point description formula of the blasting-related visual feature is:

[0076] ;

[0077] in, It 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 direction of motion of the fragment feature points, is the scale of the fragment feature points, is the difference Gaussian function, i is the different fragment scale levels, and n is the number of levels in the scale space.

[0078] The differential Gaussian function is used to detect the extreme points in the scale space and the movement direction of the fragment feature points 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.

[0079] In Example 5, in step 4, the movement trajectory of the feature points is represented by color coding or connecting lines, and the output change map is in PNG or JPEG format.

[0080] Color coding and line connections provide intuitive feature point movement trajectories, enabling analysts to quickly understand and analyze the dynamic behavior of fragments or feature points. Differentiating between feature points or fragments using different colors or line types helps clearly display multiple trajectories, avoids confusion, and facilitates communication. PNG or JPEG images are easy to share and embed in reports, facilitating communication of analysis results within a team or with other stakeholders.

[0081] In Example 6, in step 3, the shooting time point of each frame image before and after the blasting is analyzed, the vibration data of multiple blasting vibration monitoring intelligent sensors 21 are analyzed respectively, and multiple groups of vibration value data corresponding to the shooting time point of each frame image are extracted respectively.

[0082] The frame rate of the high-speed camera 11 can be selected to reach 1000 frames per second or even higher. If a frame rate of 1000 frames per second is used, 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 vibration data processing is performed corresponding to the shooting time point of each frame of image to provide data support for the data synchronization of the subsequent blasting vibration monitoring diagram.

[0083] Example 7, in step 5, visual radial lines are generated according to the radial lines arranged by the vibration sensor array 2, and the geometric center of each blasting vibration monitoring intelligent sensor 21 is mapped to the corresponding position of the visual radial line to form multiple data nodes, and a data display frame is set at each data node. Then, the time-series-based vibration data extracted in step 3 is mapped to multiple data display frames to form a vibration data time series diagram.

[0084] Radial visualization can intuitively display the spatial relationship between the vibration sensor array and the blasting point, helping analysts understand the impact of sensor layout on data acquisition. Mapping the geometric center of each sensor onto the visualized radial lines ensures a one-to-one correspondence between vibration data and the actual sensor location, improving the accuracy of data analysis. Combining visual feature changes with vibration data time series diagrams provides multi-dimensional data analysis, which helps to fully understand the impact of the blasting process. By displaying data from all sensors within the same visual frame, comparisons between vibration data captured by different sensors become simple and quick. The data display frame can update vibration data in real time, allowing monitoring personnel to track vibration changes during the blasting process in real time. Mapping vibration data directly to the graphical interface reduces data analysis time and improves the efficiency of data interpretation. By observing vibration data from sensors in different locations, the impact of blasting on different areas can be evaluated, providing a basis for risk assessment.

[0085] In Example 8, the vibration data is three-dimensional vibration speed and vibration frequency.

[0086] Example 9, a blasting vibration monitoring system based on visual and vibration sensors, used to implement a blasting vibration monitoring method based on visual and vibration sensors, the blasting vibration monitoring system includes an aerial visual monitoring device 1, a vibration sensor array 2, a blasting vibration analysis module 3 and an NTP server 4, the aerial visual 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 mission payload platform at the bottom of the drone 12, with the lens facing downward and facing the blasting point 100, the high-speed camera 11 is respectively connected to the blasting vibration analysis module 3 and the NTP server 4 via a wireless communication network, the vibration sensor array 2 includes multiple vibration monitoring mounting plates 22 and multiple blasting vibration monitoring smart sensors 21, multiple vibration monitoring mounting plates 22 are radially placed around the blasting point 100, multiple blasting vibration monitoring smart sensors 21 are respectively installed on the upper surfaces of multiple vibration monitoring mounting plates 22, and are respectively communicated with the blasting vibration analysis module 3 and the NTP server 4 through the 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 connected to the high-speed camera 11 and the multiple blasting vibration monitoring smart sensors 21 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.

[0087] In Example 10, the geometric center of the blasting point 100 is taken as the origin, and the eight direction lines due east, southeast, due south, southwest, due west, northwest, due north and northeast of the origin are taken as radial lines. Eight blasting vibration monitoring intelligent sensors 21 are arranged on the eight radial lines two meters in diameter from the origin of the blasting point 100, and then 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.

[0088] The adoption of a radial blasting monitoring layout in eight directions can provide a more comprehensive understanding of the impact of blasting on the surrounding areas.

[0089] Specific Example: A city is currently carrying out an infrastructure construction project involving rock blasting. To ensure the safety and effectiveness of the blasting, the project team decided to use a blasting vibration monitoring system based on visual and vibration sensors to monitor the blasting process.

[0090] 50 meters directly above the blasting point 100, the project team deployed a drone 12 equipped with a high-speed camera 11, ensuring that the camera lens was facing downward towards the blasting point 100.

[0091] Vibration sensor arrays 2 are radially arranged around the blasting point 100 along eight directional lines (due east, southeast, due south, southwest, due west, northwest, due north, and northeast). A blasting vibration monitoring intelligent sensor 21 is placed every five meters on each directional line, with the farthest distance from the blasting point being 102 meters.

[0092] Through the wireless network, all blasting vibration monitoring smart sensors 21 and high-speed cameras 11 are connected to the NTP server 4 for time synchronization to ensure that the time deviation of all devices is within 1 millisecond.

[0093] Before blasting, the high-speed camera 11 and all blasting vibration monitoring intelligent sensors 21 are started to collect image data and vibration data.

[0094] 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.

[0095] The collected data is transmitted to the blasting vibration analysis module 3 in real time via a wireless network.

[0096] The blasting is performed while the high-speed camera 11 and the vibration sensor 21 continue to record data.

[0097] 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 fragments with a diameter greater than 0.5 cm.

[0098] The blasting vibration analysis module 3 performs time series analysis on the vibration data collected by the vibration sensor 21 and extracts the vibration speed and frequency changes of each sensor before and after the blasting.

[0099] The blasting vibration analysis module 3 uses image processing software to draw a feature point matching diagram based on the extracted visual feature data and outputs a schematic diagram of the associated visual feature changes.

[0100] The blasting vibration analysis module 3 draws a vibration data time series diagram based on the time series analysis results, and sets a data display frame at the position of each vibration sensor 21.

[0101] The vibration data time series diagram is superimposed on the associated visual feature change diagram to form a blasting vibration monitoring diagram.

[0102] The monitoring diagram shows that the fragments produced by the explosion mainly flew to the southeast, with a maximum flight distance of about 80 meters.

[0103] The vibration data time series diagram shows that the ground vibration caused by blasting is strongest in the southeast direction, but the vibration at all monitoring points is within the safety threshold.

[0104] The project team adjusted the subsequent blasting plan based on the monitoring results, added a buffer zone in the southeast direction, and appropriately reduced the amount of explosives used.

[0105] The project team successfully used a blasting vibration monitoring system based on vision and vibration sensors to improve the safety and efficiency of blasting operations.

[0106] The above are all preferred embodiments of the present invention, and are not intended to limit the scope of protection of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A blasting vibration monitoring method based on vision and vibration sensors, characterized by: An aerial visual monitoring device (1) is arranged at a predetermined height directly above a blasting point (100), and a vibration sensor array (2) is radially arranged around the blasting point (100). The visual monitoring device (1) and the vibration sensor array (2) are wirelessly 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 blasting vibration monitoring intelligent sensors (21) of the vibration sensor array (2), start the high-speed camera (11) of the aerial visual monitoring device (1), and synchronize time between all blasting vibration monitoring intelligent sensors (21) and the high-speed camera (11) of the aerial visual monitoring device (1) based on a 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 via a wireless network; Step 3, start 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 the 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) uses image processing software to draw a feature point matching graph based on the blasting-related visual feature change data extracted in step 3, and outputs a schematic diagram of the related visual feature change; Step 5, the blasting vibration analysis module (3) performs time series 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 series diagram, and superimposes the vibration data time series diagram on the associated visual feature change diagram to form a blasting vibration monitoring diagram; The feature point description formula of the blasting correlation visual feature is: ； in, It 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 direction of motion of the fragment feature points, is the scale of the fragment feature points, is the difference Gaussian function, i is the different fragment scale levels, and n is the number of levels in the scale space.

2. The blasting vibration monitoring method based on vision and vibration sensors according to claim 1 is characterized in that: 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 camera (11) of the aerial visual monitoring device (1) and all blasting vibration monitoring intelligent sensors (21) of the vibration sensor array (2) are connected to the NTP server (4) through the wireless network. Before starting the blasting, the time of the NTP server (4) is queried for time synchronization.

3. The blasting vibration monitoring method based on vision and vibration sensors according to claim 1 is characterized in that: In step 3, the SIFT algorithm is used to extract the blast-related visual features and position coordinates in each frame of image before and after the blast. The blast-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 1 is characterized in that: In step 4, the movement trajectory of the feature points is represented by color coding or connecting lines, and the output change map is in PNG or JPEG format.

5. The blasting vibration monitoring method based on vision and vibration sensors according to claim 1 is characterized in that: In step 3, the shooting time point of each frame image before and after the blasting is analyzed, the vibration data of multiple blasting vibration monitoring intelligent sensors (21) are analyzed respectively, and multiple groups of vibration value data corresponding to the shooting time point of each frame image are extracted respectively.

6. The blasting vibration monitoring method based on vision and vibration sensors according to claim 1, characterized in that: In step 5, a visual radial line is generated according to the radial lines arranged by the vibration sensor array (2), and the geometric center of each blasting vibration monitoring intelligent sensor (21) is mapped to the corresponding position of the visual radial line to form a plurality of data nodes. A data display frame is set at each data node, and then the time-series-based vibration data extracted in step 3 is mapped to the plurality of data display frames to form a vibration data time series diagram.

7. The blasting vibration monitoring method based on vision and vibration sensors according to claim 1, characterized in that: The vibration data are three-dimensional vibration speed and vibration frequency.

8. Blasting vibration monitoring system based on vision and vibration sensors, characterized by: The blasting vibration monitoring method based on vision and vibration sensors is used to implement any one of claims 1 to 7. The blasting vibration monitoring system comprises an aerial visual monitoring device (1), a vibration sensor array (2), a blasting vibration analysis module (3) and an NTP server (4). The aerial visual monitoring device (1) comprises an unmanned aerial vehicle (12) and a high-speed camera (11). The unmanned aerial vehicle (12) flies at a set height directly above the blasting point (100). The high-speed camera (11) is mounted on the mission load platform at the bottom of the unmanned aerial vehicle (12), with the lens facing downwards towards the blasting point (100). The high-speed camera (11) is respectively connected to the blasting vibration analysis module (3) and the NTP server (4) via a wireless communication network. The vibration sensor array (2) comprises a plurality of vibration monitoring mounting plates (22) and A plurality of blasting vibration monitoring intelligent sensors (21) and a plurality of vibration monitoring mounting plates (22) are radially placed around the blasting point (100), and 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 respectively connected to the blasting vibration analysis module (3) and the NTP server (4) via 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 connected to the high-speed camera (11) and the plurality of blasting vibration monitoring intelligent sensors (21) via 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).

9. The blasting vibration monitoring system based on vision and vibration sensors according to claim 8, characterized in that: With the geometric center of the blasting point (100) as the origin, and with the eight directional lines of the origin, namely, due east, southeast, due south, southwest, due west, northwest, due north and northeast, as radial lines, eight blasting vibration monitoring intelligent sensors (21) are arranged on the eight radial lines two meters in diameter from the origin of the blasting point (100), and eight blasting vibration monitoring intelligent sensors (21) are arranged every five meters thereafter. The farthest blasting vibration monitoring intelligent sensor (21) is 102 meters away from the origin.

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