A device and method for monitoring surface subsidence around blasting points along a subway line

Abstract

This invention relates to the field of settlement monitoring technology, specifically to a device and method for monitoring surface settlement around blasting points along a subway line. The method analyzes the historical continuous collapse patterns of monitoring points to determine the potential impact of historical continuous collapses on the current situation, and identifies monitoring points exhibiting continuous collapse characteristics. It then clusters monitoring points with high settlement at the current time, determining the severity of current settlement based on the impact of continuous collapses within the clusters and the blasting energy. By combining the clustering patterns with the degree of expansion and addition in previous time periods, along with the severity of settlement and the settlement amount at the monitoring points, the invention assesses hazard indicators for monitoring. This invention improves the accuracy and reliability of the system by comprehensively assessing the overall risk of historical and regional settlement changes around the blasting point, and by integrating the current settlement amount with the risk assessment.

Description

Technical Field

[0001] This invention relates to the field of settlement monitoring technology, specifically to a device and method for monitoring surface settlement around blasting points along a subway line. Background Technology

[0002] Monitoring of surface subsidence around blasting sites along the subway line combines multiple monitoring technologies, including ground observation, satellite remote sensing, and automated monitoring systems, to achieve high-precision and high-efficiency monitoring. Simultaneously, it is essential to strengthen the deployment of monitoring points, adjust monitoring frequencies, process and analyze data, and establish a comprehensive alarm mechanism to ensure the safety and stability of subway construction. By continuously optimizing monitoring technologies and methods, the risks posed by surface subsidence can be effectively prevented and controlled, ensuring the safe operation of urban infrastructure.

[0003] In general surface subsidence monitoring, subsidence thresholds are often used to trigger alarms for abnormalities. However, since monitoring data may be affected by various factors, such as short-term geological changes and construction activities, relying solely on subsidence thresholds may lead to misjudgments of normal fluctuations, thereby triggering unnecessary alarms. Furthermore, if the subsidence amount does not reach the set threshold, but has already posed a threat to the safety of the geological structure, the monitoring method that relies solely on subsidence thresholds may not be able to detect potential risks in a timely manner, resulting in poor surface subsidence monitoring results. Summary of the Invention

[0004] To address the technical problems existing in the prior art, the present invention aims to provide a device and method for monitoring surface subsidence around blasting points along subway lines. The specific technical solution adopted is as follows:

[0005] This invention provides a method for monitoring surface subsidence around blasting points along a subway line, the method comprising:

[0006] Acquire the location information of each monitoring point and the settlement amount at each sampling time after blasting, as well as the blasting energy at the blasting point;

[0007] At each monitoring point, instantaneous collapse moments with abrupt changes in settlement over historical time series are selected; based on the degree of clustering and distribution of instantaneous collapse moments over time series and the rate of change in settlement, the current collapse impact of each monitoring point is obtained; based on the current collapse impact, continuous collapse points are selected from the monitoring points;

[0008] At the current moment, high settlement points are identified among the monitoring points, and clusters are obtained based on the location information of the high settlement points. The settlement severity of the high settlement clusters is obtained based on the distribution of continuous collapse points and the blasting energy of the blasting points in each high settlement cluster.

[0009] Based on the degree of expansion and addition of the high settlement clusters at the current time compared to the previous sampling time, the settlement change index at the current time is obtained; based on the settlement amount of each monitoring point at the current time, combined with the settlement severity when it is in the high settlement cluster and the settlement change index, the hazard index of each monitoring point is obtained.

[0010] At the current moment, monitoring is conducted based on hazard indicators from all monitoring points.

[0011] Furthermore, the method for obtaining the instantaneous collapse moment includes:

[0012] For any monitoring point, the difference in settlement between each sampling time and the previous sampling time is normalized and used as the collapse amount of the monitoring point at each sampling time;

[0013] The sampling time when the collapse volume of the monitoring point in the historical time series exceeds the preset collapse threshold is taken as the instantaneous collapse time of the monitoring point.

[0014] Furthermore, the method for obtaining the current collapse impact includes:

[0015] For any monitoring point, all instantaneous collapse moments in the historical time series of that monitoring point are clustered according to the degree of approximation of the time distribution to obtain a time cluster;

[0016] Within each time-series cluster, the ratio of the sum of all settlement values ​​between the initial instantaneous collapse time and the final instantaneous collapse time to the time difference is taken as the collapse rate of each time-series cluster; the average of the collapse rates of all time-series clusters is taken as the collapse rate influence index of that monitoring point.

[0017] By negatively correlating the time difference between the last instantaneous collapse moment in the historical timeline of the monitoring point and the current moment, the collapse time impact index of the monitoring point is obtained.

[0018] The ratio of the total number of instantaneous collapse moments in the historical time series of the monitoring point to the total number of all sampling moments is used as the collapse distribution impact index of the monitoring point.

[0019] By combining the collapse rate impact index, collapse time impact index, and collapse distribution impact index of the monitoring point, the current collapse impact degree of the monitoring point is obtained.

[0020] Furthermore, the method for determining the high settlement point includes:

[0021] If the normalized value of the settlement at the current monitoring point is greater than the preset high settlement threshold, the corresponding monitoring point will be designated as a high settlement point.

[0022] Furthermore, the method for obtaining the severity of settlement includes:

[0023] For any high settlement cluster, the product of the maximum settlement amount in the high settlement cluster and the number of high settlement points is taken as the regional settlement degree of the high settlement cluster; the product of the number of continuous collapse points in the high settlement cluster and the regional settlement degree is normalized and taken as the collapse severity of the high settlement cluster.

[0024] For any high settlement cluster, convex hull detection is performed based on the location information of the high settlement points in the high settlement cluster to obtain the convex hull region of the high settlement cluster; the sum of the blasting energy of the blasting points contained in the convex hull region is normalized to obtain the blasting severity of the high settlement cluster.

[0025] The settlement severity of the high-settlement cluster is obtained by combining the collapse severity and blasting severity of the high-settlement cluster.

[0026] Furthermore, the method for obtaining the abrupt settlement change index includes:

[0027] Obtain the high settlement points at the previous sampling time. Take the intersection of the high settlement points at the current time and the previous sampling time, and use the high settlement points in the intersection as the intersection point. If there are high settlement points in the high settlement cluster at the current time that are not completely intersection points, the corresponding high settlement cluster will be used as an extended cluster. If there are no intersection points in the high settlement cluster at the current time, the corresponding high settlement cluster will be used as a new cluster.

[0028] Calculate the ratio of the total number of intersection points in each expanded cluster to the total number of all high settlement points, and use it as the expansion degree of each expanded cluster; normalize the sum of the expansion degrees of all expanded clusters, and use it as the expansion index at the current moment.

[0029] Normalize the sum of high-settlement points in all newly added clusters to obtain the new index at the current moment;

[0030] By combining the extended and newly added indicators at the current moment, the abrupt change in settlement indicators at the current moment can be obtained.

[0031] Furthermore, the method for obtaining the hazard indicator includes:

[0032] The product of the settlement severity and the settlement change index of each high settlement cluster is used as the risk factor for each high settlement cluster; the risk level of each non-high settlement point is recorded as the preset low risk value.

[0033] The ratio of the settlement amount of each high settlement point to the maximum settlement amount in its high settlement cluster is taken as the relative settlement degree of each high settlement point; the product of the relative settlement degree of each high settlement point and the risk factor of its high settlement cluster is normalized to obtain the risk increase degree of each high settlement point; the sum of the risk increase degree of each high settlement point and the preset low risk value is taken as the risk degree of each high settlement point.

[0034] The product of the settlement amount and risk level at each monitoring point at the current moment is normalized and used as the hazard indicator for each monitoring point.

[0035] Furthermore, the monitoring of hazard indicators based on all monitoring points includes:

[0036] If the hazard index of a monitoring point at the current moment exceeds the preset hazard threshold, the corresponding monitoring point will be recorded as an abnormal monitoring point and a monitoring report will be generated.

[0037] Furthermore, the method for obtaining the continuous collapse point includes:

[0038] When the normalized value of the current collapse impact at a monitoring point is greater than the preset impact threshold, the corresponding monitoring point is recorded as a continuous collapse point.

[0039] The present invention also provides a surface subsidence monitoring device for the area surrounding a blasting point along a subway line, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the surface subsidence monitoring method for the area surrounding a blasting point along a subway line as described in any of the above.

[0040] The present invention has the following beneficial effects:

[0041] This invention considers the ongoing settlement process following blasting, analyzes the continuous collapse of monitoring points over historical timelines, determines the potential impact of historical continuous collapses on the current situation, and filters out monitoring points exhibiting continuous collapse characteristics to more comprehensively assess the potential risk level of subsequent settlement. Since settlement typically occurs over a wide area, location clustering is performed on monitoring points with high settlement at the current moment to analyze the overall situation of the settlement area. Based on the impact of continuous collapses within the clusters and the influence of blasting energy, a preliminary analysis of the current potential settlement severity is conducted. Furthermore, the potential for blasting damage to exacerbate settlement is considered, leading to a more comprehensive risk assessment. By comparing the extent of expansion and addition with previous timelines, and combining the settlement severity of the high-settlement clusters where the monitoring points are located, the risk assessment method that relies solely on settlement volume is optimized, resulting in a comprehensive assessment of the risk level for monitoring. This invention assesses the overall risk of historical and regional subsidence changes around the blasting point by combining the current subsidence at the monitoring point with the risk assessment. This reduces the impact of misjudgments caused by short-term geological changes or construction activities, as well as the failure to promptly identify dangers that have actually threatened the safety of the geological structure, thereby improving the accuracy and reliability of the system monitoring. Attached Figure Description

[0042] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 A flowchart of a method for monitoring surface subsidence around blasting points along a subway line, provided as an embodiment of the present invention;

[0044] Figure 2 This is a schematic diagram of a settlement curve after blasting, provided as an embodiment of the present invention. Detailed Implementation

[0045] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a surface subsidence monitoring device and method for areas adjacent to blasting points along a subway line, as proposed by the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0046] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0047] The following description, in conjunction with the accompanying drawings, details the specific scheme of a surface subsidence monitoring device and method for locations adjacent to blasting points along a subway line, provided by the present invention.

[0048] Please see Figure 1 The diagram illustrates a flowchart of a method for monitoring surface subsidence around a blasting point along a subway line, according to an embodiment of the present invention. The method includes the following steps:

[0049] S1: Obtain the location information of each monitoring point and the settlement amount at each sampling time after blasting, as well as the blasting energy at the blasting point.

[0050] Before the blasting, monitoring points will be pre-buried around the blasting point along the subway line. This involves using a rapid drilling device to pre-drill monitoring holes around the blasting point, embedding the support pipe into the stratum using arc-shaped claws, and obtaining the location coordinates of each monitoring point, such as latitude and longitude.

[0051] During blasting, explosives are pre-buried at the designated coordinates of each blast point. The amount and type of explosives are prepared in advance, and each type of explosive corresponds to a specific explosive yield, which is a commonly used indicator to measure the power of explosives. For example, one gram of TNT releases approximately 4184 joules of energy when detonated. Therefore, by multiplying the amount of explosives at each blast point by its explosive yield, the blast energy at that blast point can be obtained.

[0052] Real-time monitoring is required after blasting. The height difference between monitoring points is measured using a hydrostatic level to determine settlement. Data is continuously collected and settlement changes are analyzed, with real-time early warnings provided via a cloud platform. In this embodiment, the data collection frequency is set to once per hour, but this can be adjusted by the implementer according to the specific implementation scenario and is not limited here. Furthermore, InSAR technology is used to re-measure and verify key areas within the blasted area to ensure data accuracy.

[0053] S2: At each monitoring point, select the instantaneous collapse moments with abrupt changes in settlement over historical time series; based on the degree of clustering and distribution of instantaneous collapse moments over time series and the rate of change in settlement, obtain the current collapse impact of each monitoring point; based on the current collapse impact, select the continuous collapse points from the monitoring points.

[0054] In monitoring surface subsidence around blasting sites adjacent to subway lines, the subsequent impacts will vary depending on the blasting point. Please refer to [link / reference needed]. Figure 2This diagram illustrates a post-blast settlement curve according to an embodiment of the present invention. Differences may exist, for example, where significant changes in the geological structure occur shortly after blasting, causing ground subsidence that eventually stabilizes. Figure 2 The settlement curve of the MIP-1 test site. The geological structural changes caused by the blasting did not reach the limit for ground subsidence; that is, there was no initial subsidence. Subsequent factors such as groundwater level fluctuations and vibrations from construction machinery exacerbated the geological structural changes, causing ground subsidence followed by a period of stabilization. Figure 2 The MICP-2 settlement curve shows that the geological structure has been changing since the blasting and cannot stabilize in a short period of time, resulting in a continuous increase in ground subsidence, as shown in the UN-1 settlement curve in Figure 2.

[0055] Therefore, by analyzing the historical changes in settlement at each monitoring point over time, the sustainability of surface collapse at each monitoring point after the blasting is determined, and the possibility of significant collapse at the monitoring point at subsequent times is assessed. If such collapse is observed, the risk of settlement is relatively high.

[0056] Therefore, the first step is to determine the moments of significant settlement changes in the historical timeline, and then screen for collapse moments with significant structural changes. In this embodiment of the invention, the method for obtaining the instantaneous collapse moment includes:

[0057] For any given monitoring point, the difference in settlement between each sampling time and the previous sampling time is normalized and used as the collapse amount at that monitoring point at each sampling time. It can be understood that the collapse amount reflects the instantaneous degree of surface collapse; the first sampling time is not analyzed. It should be noted that normalization is a technique well-known to those skilled in the art, and the choice of normalization can be linear normalization or standard normalization, etc. The specific normalization method is not limited here.

[0058] Then, the sampling time when the collapse amount of the monitoring point in the historical time series is greater than the preset collapse threshold is taken as the instantaneous collapse time of the monitoring point. When the instantaneous collapse degree is high, it reflects that there is still a collapse at the current time, and the time is recorded as the instantaneous collapse time. In this embodiment of the invention, the preset collapse threshold is set to 0.3. The specific value can be adjusted by the implementer and is not limited here.

[0059] By analyzing the distribution of instantaneous collapse moments over historical time, the more severe the collapse is when there is a clustering of instantaneous collapse moments, the more severe the damage to the surface after the blasting is, and the greater the impact on the current monitoring point may be. Therefore, further analysis of the clustered collapses over time is needed to assess the impact of historical collapses at the monitoring point on the present.

[0060] Preferably, in this embodiment of the invention, the method for obtaining the current collapse impact includes:

[0061] First, for any given monitoring point, all instantaneous collapse moments in the historical timeline of that monitoring point are clustered based on the similarity of their temporal distribution, resulting in time-based clusters. In this embodiment of the invention, the time interval between any two instantaneous collapse moments is used as the clustering distance. The DBSCAN clustering algorithm is then used to cluster all instantaneous collapse moments, resulting in multiple time-based clusters. Each time-based cluster represents one surface collapse process. It should be noted that the clustering algorithm is a technique well-known to those skilled in the art and will not be elaborated upon here.

[0062] Furthermore, within each time-series cluster, the ratio of the sum of all settlement values ​​between the initial and final instantaneous collapse times to the time difference is used as the collapse rate of each time-series cluster. In any time-series cluster, the ratio of the total settlement between the first and last instantaneous collapse times to the time interval reflects the rate of a single collapse process. The faster the collapse rate, the more severe the damage to the geological structure.

[0063] Therefore, the average collapse rate of all clusters at all times is used as the collapse rate influence index of the monitoring point. The larger the collapse rate influence index, the faster the collapse in the historical time series, the higher the possibility of destruction, and the greater the current subsidence risk of the monitoring point.

[0064] Furthermore, by negatively correlating the time difference between the last instantaneous collapse moment in the historical timeline of the monitoring point and the current moment, an impact index on the collapse time of the monitoring point is obtained. The closer the last instantaneous collapse moment is to the current moment, the higher the risk of the surface collapse situation affecting the subsequent current moment. It should be noted that the negative correlation mapping is a technique well-known to those skilled in the art, such as using an inverse proportional relationship or a negative exponential form with a natural constant as the base, etc., and will not be elaborated or limited here.

[0065] Furthermore, the ratio of the total number of instantaneous collapse moments in the historical time series of the monitoring point to the total number of all sampling moments is used as the collapse distribution influence index of the monitoring point. The larger the proportion of instantaneous collapse moments in the historical time series of the monitoring point, the stronger the continuity of historical collapses and the higher the current risk of the monitoring point.

[0066] Therefore, by combining the collapse rate impact index, collapse time impact index, and collapse distribution impact index of the monitoring point, the current collapse impact degree of the monitoring point is obtained. In a specific embodiment of the present invention, the product of the collapse rate impact index, collapse time impact index, and collapse distribution impact index of the monitoring point is used as the current collapse impact degree of the monitoring point. The product of the three reflects the impact of continuous collapse at the surface monitoring point after blasting on the current situation.

[0067] The greater the current collapse impact, the higher the probability of a collapse at the monitoring point at that moment, and the greater the risk of anomaly analysis. Furthermore, based on the magnitude of the current collapse impact, unstable monitoring points are screened for subsequent analysis. In this embodiment of the invention, when the normalized value of the current collapse impact of a monitoring point is greater than a preset impact threshold, the corresponding monitoring point is recorded as a continuously collapsing point, and the remaining monitoring points are considered relatively stable. The preset impact threshold is set to 0.7, and the specific value can be adjusted by the implementer.

[0068] S3: Identify the high settlement points among the monitoring points at the current moment, and cluster them according to the location information of the high settlement points to obtain high settlement clusters; obtain the settlement severity of the high settlement clusters based on the distribution of continuous collapse points and the blasting energy of the blasting points in each high settlement cluster.

[0069] After analyzing the historical subsidence changes at each monitoring point, considering the regional extent of surface subsidence (e.g., large-area subsidence, localized small-area subsidence), the risks inherent in different subsidence areas vary. Furthermore, the energy levels at different blasting points differ, leading to varying degrees of structural damage. Therefore, further analysis of the risks at monitoring points with high subsidence at the current time is conducted to ensure more accurate risk assessments at subsequent monitoring points.

[0070] First, monitoring points with high settlement are selected for analysis. These monitoring points may be subject to various environmental changes that may cause high settlement. In this embodiment of the invention, if the normalized value of the settlement of the monitoring point at the current moment is greater than the preset high settlement threshold, the corresponding monitoring point is designated as a high settlement point. The preset high settlement threshold can be set to 0.5. The normalization process can be performed using the minimum-maximum normalization method. Monitoring points with a normalized value greater than 0.5 are recorded as high settlement points, and those with a normalized value less than 0.5 are recorded as low settlement points.

[0071] To perform regional analysis, clustering is performed based on the location information of high settlement points to obtain high settlement clusters. Each high settlement cluster represents a concentrated area of ​​a single high settlement point at the current time. In this embodiment of the invention, the Euclidean distance between high settlement points is obtained based on the location coordinates of each high settlement point. The K-means clustering algorithm is then used to cluster all high settlement points, resulting in multiple high settlement clusters corresponding to the current time. It should be noted that the K-means clustering algorithm is a well-known technique to those skilled in the art and will not be elaborated upon here.

[0072] Large-scale severe subsidence is often caused by blasting that severely damages the stability of the geological structure. Therefore, by analyzing the blasting effect and the continuous collapse of the subsidence in the area corresponding to each high subsidence cluster at the current moment, the severity of subsidence in the area corresponding to the cluster can be obtained.

[0073] Preferably, in this embodiment of the invention, the method for obtaining the severity of settlement includes:

[0074] First, for any high settlement cluster, the product of the maximum settlement amount in the high settlement cluster and the number of high settlement points is taken as the regional settlement degree of the high settlement cluster. The larger the maximum settlement amount in the cluster and the more monitoring points it contains, the greater the risk and the more severe the settlement.

[0075] The product of the number of continuous collapse points in the high settlement cluster and the regional settlement degree is normalized and used as the collapse severity of the high settlement cluster. The more continuous collapse points there are, the more likely the high settlement cluster is to continue to settle, and the greater the risk. Therefore, the collapse severity is obtained by combining the regional settlement degree, which reflects the severity of the regional settlement risk.

[0076] Furthermore, for any high subsidence cluster, convex hull detection is performed based on the location information of the high subsidence points within the cluster to obtain the convex hull region of the high subsidence cluster. The convex hull region can characterize the regional distribution size of a single high subsidence point on the surface. In this embodiment of the invention, when the location information is latitude and longitude, a planar coordinate system is constructed with latitude and longitude as the horizontal and vertical axes, and the high subsidence points are mapped onto the planar coordinate system. The convex hull detection algorithm is then used to obtain the convex hull region of each high subsidence cluster. It should be noted that the convex hull detection algorithm is a well-known technique to those skilled in the art and will not be elaborated upon here.

[0077] The sum of the blasting energies of the blasting points within the convex hull region is normalized to obtain the blasting severity of the high settlement cluster. When the location information of the blasting point is within the convex hull region, the blasting at the blasting point is considered to have a high degree of impact on the current settlement area. The degree of damage is reflected by combining all the blasting energies at the time of blasting. The greater the blasting severity, the greater the destructive impact of the blasting on the area, and the higher the risk of subsequent settlement in the area.

[0078] Finally, by combining the collapse severity and blasting severity of the high settlement cluster, the settlement severity of the high settlement cluster is obtained. In this embodiment of the invention, the product of the collapse severity and blasting severity of the high settlement cluster is used as the settlement severity of the high settlement cluster. The severity of regional settlement is assessed in conjunction with the impact of blasting and historical collapse. The greater the settlement severity, the greater the risk to the area corresponding to the cluster.

[0079] S4: Based on the degree of expansion and addition of the distribution of high settlement clusters at the current time compared to the previous sampling time, obtain the settlement change index at the current time; based on the settlement amount of each monitoring point at the current time, combined with the settlement severity when in the high settlement cluster and the settlement change index, obtain the hazard index of each monitoring point.

[0080] Since some of the high settlement clusters at the current moment are newly emerging settlement areas, while others are settlement areas that have expanded or deepened on the basis of existing settlement areas, the impact of these two phenomena on the surface settlement around the blasting point adjacent to the subway line is completely different. Therefore, it is necessary to comprehensively determine the surface settlement risk around the blasting point at the current moment based on these two phenomena.

[0081] By comparing and analyzing the degree of amplification with the previous sampling time, the degree of current abrupt change is reflected. Preferably, in this embodiment of the invention, the method for obtaining the abrupt settlement change index includes:

[0082] First, obtain the high settlement points at the previous sampling time. Then, find the intersection of the high settlement points at the current time and the previous sampling time, and use the high settlement points in the intersection as the intersection point. If there are high settlement points in the high settlement cluster at the current time that are not completely intersection points, it means that there are newly added higher settlement points in the cluster at the current time, and the corresponding high settlement cluster is taken as the extended cluster.

[0083] If the high settlement cluster at the current moment does not contain any intersection points, it indicates that the cluster at the current moment is a newly emerging settlement area, and the corresponding high settlement cluster will be treated as a new cluster. It is understandable that if all the high settlement points in the high settlement cluster at the current moment are intersection points, it indicates that the cluster at the current moment has not expanded, does not have a sudden change effect, and is not included in the sudden change analysis.

[0084] Furthermore, the ratio of the total number of intersection points in each expanded cluster to the total number of all high settlement points is calculated as the expansion degree of each expanded cluster. A larger expansion degree indicates that the settlement area corresponding to the original cluster has expanded significantly, and the surface settlement change is greater. The sum of the expansion degrees of all expanded clusters is normalized and used as the expansion index at the current moment, reflecting the current overall expansion of the settlement area.

[0085] Furthermore, the sum of high subsidence points in all newly added clusters is normalized to obtain the new index at the current moment. The larger the new index, the larger the new subsidence area and the greater the change in surface subsidence.

[0086] Finally, by combining the extended and newly added indicators at the current moment, the settlement change index at the current moment is obtained. In this embodiment of the invention, the extended and newly added indicators at the current moment are weighted and summed to obtain the settlement change index at the current moment. The appearance of new settlement areas indicates that there may be reasons that damage the geological structure, such as changes in groundwater or the impact of underground construction, which means that there is a significant impact and requires more attention. On the other hand, the extended cluster of high settlement areas appears on the basis of the original, which may be a smaller impact that exacerbates the original problem. Therefore, it can be given a smaller attention weight. Thus, the weight of the extended indicator is set to 0.4 and the weight of the newly added indicator is set to 0.6. The implementer can adjust the specific values ​​according to the specific implementation scenario.

[0087] The current overall settlement change index reflects the potential risks from various construction environment factors at the current moment. Combined with the severity of risks at individual high settlement clusters, risk factors at high settlement points are comprehensively adjusted. In conjunction with standard anomaly detection—that is, immediately activating the anomaly response mechanism when abnormal data is detected, such as settlement exceeding limits—more sensitive and accurate hazard indicators are assessed at monitoring points.

[0088] Preferably, in this embodiment of the invention, the method for obtaining the hazard indicator includes:

[0089] First, the product of the settlement severity and the settlement change index of each high settlement cluster is used as the risk factor for each high settlement cluster. Based on the risk assessment of the comprehensive settlement analysis, the larger the settlement severity and the settlement change index, the higher the settlement severity of the area corresponding to the high settlement cluster, and the larger the overall settlement change affected by factors at the current moment. The risk of settlement anomaly at the monitoring point may be higher.

[0090] For non-high settlement points at the current moment, their settlement changes may be less affected and no adjustment is required. The risk level of each non-high settlement point is recorded as a preset low risk value. In this embodiment of the invention, the preset low risk value is set to 1.

[0091] Furthermore, the ratio of the settlement amount of each high settlement point to the maximum settlement amount in the high settlement cluster is taken as the relative settlement degree of each high settlement point. When the settlement amount of a high settlement point is closer to the maximum settlement amount of the high settlement cluster, it indicates that the second highest settlement point is more likely to be located in the center or key position of the settlement area, and the greater the credibility of risk control.

[0092] Therefore, the product of the relative settlement degree of each high settlement point and the risk factor of the high settlement cluster is normalized to obtain the risk increase degree of each high settlement point. Combined with the risk assessment of the high-risk cluster, the larger the risk factor, the greater the possibility of abnormal risks arising from the interference factors in the area where the monitoring point is located. The larger the relative settlement degree, the more critical the area where the monitoring point is located, and the more reliable the risk impact assessment. Therefore, the greater the risk increase degree of the monitoring point as a high settlement point, the higher the degree of dangerous anomaly of the monitoring point.

[0093] Furthermore, the sum of the risk increment of each high settlement point and the preset low risk value is used as the risk level of each high settlement point. The risk assessment level is incremented on the low risk level to obtain a more sensitive risk level for high settlement points.

[0094] Finally, by combining the settlement amount from the basic early warning, the product of the settlement amount and the risk level at each monitoring point at the current moment is normalized and used as a hazard indicator for each monitoring point. The higher the hazard indicator, the more abnormal the monitoring point is.

[0095] S5: At the current moment, monitor the hazard indicators based on all monitoring points.

[0096] The higher the hazard index, the more significant the possible settlement anomaly at the monitoring point. Monitoring is carried out based on the hazard index of all monitoring points. In this embodiment of the invention, if the hazard index of the monitoring point at the current moment is greater than the preset hazard threshold, the corresponding monitoring point is recorded as an abnormal monitoring point and a monitoring report is generated. The preset hazard threshold is set to 0.8, and the specific value can be adjusted by the implementer.

[0097] After identifying the abnormal monitoring point, in one embodiment of the present invention, a professional team can be organized to conduct on-site investigations of the abnormal monitoring point, collect more geological, hydrological, and construction information, determine the potential threat of the abnormal point to subway operation and public safety, and assess possible chain reactions and secondary disaster risks. Intervention measures can be implemented to ensure operational safety, avoid creating new risks, and subsequently strengthen monitoring by increasing the frequency and density of monitoring the abnormal monitoring point and its surrounding area to more accurately grasp the subsidence development trend. The intervention measures taken can be continuously tracked and evaluated to ensure their effectiveness, and response strategies can be adjusted based on subsequent monitoring data.

[0098] In summary, this invention considers the ongoing settlement process after blasting, analyzes the continuous collapse of monitoring points over historical timelines, determines the potential impact of historical continuous collapses on the current situation, and filters out monitoring points exhibiting continuous collapse characteristics to more comprehensively assess the potential risk level of subsequent settlement. Since settlement typically occurs over a wide area, location clustering is performed on monitoring points with high settlement at the current moment to analyze the overall situation of the settlement area. Based on the impact of continuous collapses within the clusters and the influence of blasting energy, a preliminary analysis of the current potential settlement severity is conducted. Furthermore, the potential for blasting damage to exacerbate settlement is considered, leading to a more comprehensive assessment of the risk. By comparing the extent of expansion and addition with previous timelines, and combining the settlement severity of the high-settlement clusters where the monitoring points are located, the assessment of risk based solely on settlement volume is optimized, resulting in a comprehensive assessment of the risk level for monitoring. This invention assesses the overall risk of historical and regional subsidence changes around the blasting point by combining the current subsidence at the monitoring point with the risk assessment. This reduces the impact of misjudgments caused by short-term geological changes or construction activities, as well as the failure to promptly identify dangers that have actually threatened the safety of the geological structure, thereby improving the accuracy and reliability of the system monitoring.

[0099] The present invention also provides a surface subsidence monitoring device for the area surrounding a blasting point along a subway line, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the surface subsidence monitoring method for the area surrounding a blasting point along a subway line as described in any of the above.

[0100] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0101] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for monitoring surface subsidence around blasting points along a subway line, characterized in that, The method includes: Acquire the location information of each monitoring point and the settlement amount at each sampling time after blasting, as well as the blasting energy at the blasting point; At each monitoring point, instantaneous collapse moments with abrupt changes in settlement over historical time series are selected; based on the degree of clustering and distribution of instantaneous collapse moments over time series and the rate of change in settlement, the current collapse impact of each monitoring point is obtained; based on the current collapse impact, continuous collapse points are selected from the monitoring points; At the current moment, high settlement points are identified among the monitoring points, and clusters are obtained based on the location information of the high settlement points. The settlement severity of the high settlement clusters is obtained based on the distribution of continuous collapse points and the blasting energy of the blasting points in each high settlement cluster. Based on the degree of expansion and addition of the high settlement clusters at the current time compared to the previous sampling time, the settlement change index at the current time is obtained; based on the settlement amount of each monitoring point at the current time, combined with the settlement severity when it is in the high settlement cluster and the settlement change index, the hazard index of each monitoring point is obtained. At the current moment, monitoring is conducted based on hazard indicators from all monitoring points.

2. The method for monitoring surface subsidence around blasting points along a subway line according to claim 1, characterized in that, The method for obtaining the instantaneous collapse moment includes: For any monitoring point, the difference in settlement between each sampling time and the previous sampling time is normalized and used as the collapse amount of the monitoring point at each sampling time; The sampling time when the collapse volume of the monitoring point in the historical time series exceeds the preset collapse threshold is taken as the instantaneous collapse time of the monitoring point.

3. The method for monitoring surface subsidence around blasting points along a subway line according to claim 1, characterized in that, The method for obtaining the current impact of the collapse includes: For any monitoring point, all instantaneous collapse moments in the historical time series of that monitoring point are clustered according to the degree of approximation of the time distribution to obtain a time cluster; Within each time-series cluster, the ratio of the sum of all settlement values ​​between the initial instantaneous collapse time and the final instantaneous collapse time to the time difference is taken as the collapse rate of each time-series cluster; the average of the collapse rates of all time-series clusters is taken as the collapse rate influence index of that monitoring point. By negatively correlating the time difference between the last instantaneous collapse moment in the historical timeline of the monitoring point and the current moment, the collapse time impact index of the monitoring point is obtained. The ratio of the total number of instantaneous collapse moments in the historical time series of the monitoring point to the total number of all sampling moments is used as the collapse distribution impact index of the monitoring point. By combining the collapse rate impact index, collapse time impact index, and collapse distribution impact index of the monitoring point, the current collapse impact degree of the monitoring point is obtained.

4. The method for monitoring surface subsidence around blasting points along a subway line according to claim 1, characterized in that, The method for determining the high settlement point includes: If the normalized value of the settlement at the current monitoring point is greater than the preset high settlement threshold, the corresponding monitoring point will be designated as a high settlement point.

5. The method for monitoring surface subsidence around blasting points along a subway line according to claim 1, characterized in that, The methods for obtaining the severity of settlement include: For any high settlement cluster, the product of the maximum settlement amount in the high settlement cluster and the number of high settlement points is taken as the regional settlement degree of the high settlement cluster; the product of the number of continuous collapse points in the high settlement cluster and the regional settlement degree is normalized and taken as the collapse severity of the high settlement cluster. For any high settlement cluster, convex hull detection is performed based on the location information of the high settlement points in the high settlement cluster to obtain the convex hull region of the high settlement cluster; the sum of the blasting energy of the blasting points contained in the convex hull region is normalized to obtain the blasting severity of the high settlement cluster. The settlement severity of the high-settlement cluster is obtained by combining the collapse severity and blasting severity of the high-settlement cluster.

6. The method for monitoring surface subsidence around blasting points along a subway line according to claim 1, characterized in that, The method for obtaining the abrupt settlement change index includes: Obtain the high settlement points at the previous sampling time. Take the intersection of the high settlement points at the current time and the previous sampling time, and use the high settlement points in the intersection as the intersection point. If there are high settlement points in the high settlement cluster at the current time that are not completely intersection points, the corresponding high settlement cluster will be used as an extended cluster. If there are no intersection points in the high settlement cluster at the current time, the corresponding high settlement cluster will be used as a new cluster. Calculate the ratio of the total number of intersection points in each expanded cluster to the total number of all high settlement points, and use it as the expansion degree of each expanded cluster; normalize the sum of the expansion degrees of all expanded clusters, and use it as the expansion index at the current moment. Normalize the sum of high-settlement points in all newly added clusters to obtain the new index at the current moment; By combining the extended and newly added indicators at the current moment, the abrupt change in settlement indicators at the current moment can be obtained.

7. The method for monitoring surface subsidence around blasting points along a subway line according to claim 1, characterized in that, The methods for obtaining the hazard indicators include: The product of the settlement severity and the settlement change index of each high settlement cluster is used as the risk factor for each high settlement cluster; the risk level of each non-high settlement point is recorded as the preset low risk value. The ratio of the settlement amount of each high settlement point to the maximum settlement amount in its high settlement cluster is taken as the relative settlement degree of each high settlement point; the product of the relative settlement degree of each high settlement point and the risk factor of its high settlement cluster is normalized to obtain the risk increase degree of each high settlement point; the sum of the risk increase degree of each high settlement point and the preset low risk value is taken as the risk degree of each high settlement point. The product of the settlement amount and risk level at each monitoring point at the current moment is normalized and used as the hazard indicator for each monitoring point.

8. The method for monitoring surface subsidence around blasting points along a subway line according to claim 1, characterized in that, The monitoring of hazard indicators based on all monitoring points includes: If the hazard index of a monitoring point at the current moment exceeds the preset hazard threshold, the corresponding monitoring point will be recorded as an abnormal monitoring point and a monitoring report will be generated.

9. The method for monitoring surface subsidence around blasting points along a subway line according to claim 1, characterized in that, The method for obtaining the continuous collapse point includes: When the normalized value of the current collapse impact at a monitoring point is greater than the preset impact threshold, the corresponding monitoring point is recorded as a continuous collapse point.

10. A surface subsidence monitoring device for the area surrounding a blasting point along a subway line, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for monitoring surface subsidence around blasting points along a subway line as described in any one of claims 1 to 9.

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