An alarm method and system for earthquake emergency response

Abstract

This invention provides an alarm method and system for earthquake emergency response, relating to the field of earthquake alarm technology. It constructs a distributed alarm network consisting of earthquake monitoring nodes, regional relay nodes, and terminal alarm nodes. After detecting the initial seismic wave signal, the earthquake monitoring nodes generate primary alarm data containing a vibration intensity threshold and a time stamp. Within a preset time window, the regional relay nodes perform path identification, path identifier generation, and reception time difference calculation on data from different transmission paths, obtaining path quantity information and time interval distribution characteristics. Based on this, they determine the time difference threshold, consistency constraints, and path independence verification, generating relay alarm data. The relay alarm data is broadcast and forwarded to form diffused alarm data. The terminal alarm nodes deduplicate the data, determine triggering, and output audible and visual alarm signals; if no relay alarm data is generated, suppression processing is performed. This method can improve alarm accuracy and reduce false alarm rate.

Description

Technical Field

[0001] This invention relates to the field of earthquake alarm technology, and in particular to an alarm method and system for emergency earthquake response. Background Technology

[0002] In existing technologies, earthquake alarms largely rely on the linkage between earthquake monitoring networks and public alarm systems. For example, seismic stations collect seismic wave data in real time, and a central server quickly calculates the magnitude, epicenter location, and intensity distribution before sending early warning information to broadcast television systems, mobile SMS platforms, or dedicated alarm terminals to achieve unified alarm coverage within the region. Simultaneously, some systems also integrate IoT terminals, deploying audible and visual alarms in key locations such as schools and hospitals. These alarms receive commands and trigger alarms via wired or wireless networks to complete the initial response to earthquake emergencies.

[0003] However, in complex scenarios such as urban underground utility tunnels or large commercial complexes, the aforementioned technologies have significant limitations. For example, during an earthquake, communication networks (such as cellular signals or Wi-Fi) in underground spaces are easily affected by structural obstructions and power outages, causing alarm commands to fail to be transmitted to terminal devices in a timely manner. In practical applications, there have been instances where some underground shopping malls failed to receive early warning information synchronously, causing people to miss the optimal evacuation opportunity. In addition, existing systems mostly rely on a central server to uniformly issue commands. Once the uplink is congested or a node fails, alarm delays or even failures will occur in some areas, reducing the reliability of the overall emergency response. Summary of the Invention

[0004] The purpose of this invention is to provide an alarm method and system for earthquake emergency response, aiming to solve the problems mentioned in the background art.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows:

[0006] In a first aspect, an alarm method for earthquake emergency response, the method comprising:

[0007] Construct a distributed alarm network consisting of earthquake monitoring nodes, regional relay nodes, and terminal alarm nodes;

[0008] When an earthquake monitoring node detects an initial seismic wave signal, it processes the initial seismic wave signal to generate primary alarm data containing a vibration intensity threshold and a time stamp, and then sends the primary alarm data to the adjacent regional relay node.

[0009] After receiving the primary alarm data, the relay nodes in each area perform statistical processing on the primary alarm data. Within a preset time window, they identify the path of the primary alarm data from different transmission paths, generate corresponding path identifiers, and calculate the reception time difference for each path to generate path quantity information and time interval distribution characteristics.

[0010] Based on the path quantity information and time interval distribution characteristics, a threshold is determined for the time difference between primary alarm data from different paths, and a consistency constraint is applied to the distribution state of the time difference based on the time interval distribution characteristics to generate effective alarm data combinations; the path independence of the effective alarm data combinations is verified to generate relay alarm data.

[0011] Each regional relay node broadcasts the relay alarm data, sending it to the terminal alarm nodes within its coverage area and forwarding it to other regional relay nodes with path identifiers, thus generating propagated alarm data.

[0012] After receiving the diffused alarm data, the terminal alarm node performs deduplication based on the path identifier and determines the trigger for non-duplicate alarm data based on the vibration intensity threshold. When the triggering condition is met, an audible and visual alarm signal is generated, and a valid alarm triggering result is obtained.

[0013] When a regional relay node fails to generate relay alarm data within a preset time window, suppression processing is performed to block alarm output.

[0014] Secondly, an alarm system for earthquake emergency response, the system comprising:

[0015] The network construction module is used to build a distributed alarm network consisting of earthquake monitoring nodes, regional relay nodes, and terminal alarm nodes.

[0016] The primary alarm generation module is used to process the initial seismic wave signal when the earthquake monitoring node detects the initial seismic wave signal, generate primary alarm data containing the vibration intensity threshold and time identifier, and send the primary alarm data to the adjacent regional relay node.

[0017] The statistical processing module is used to perform statistical processing on the primary alarm data after the relay nodes in each area receive the primary alarm data. Within a preset time window, it identifies the path of the primary alarm data from different transmission paths, generates the corresponding path identifier, calculates the reception time difference for each path, and generates path quantity information and time interval distribution characteristics.

[0018] The judgment generation module is used to determine the threshold of the time difference between primary alarm data from different paths based on the path quantity information and time interval distribution characteristics, and to impose consistency constraints on the distribution state of the time difference based on the time interval distribution characteristics to generate valid alarm data combinations; and to perform path independence verification on the valid alarm data combinations to generate relay alarm data.

[0019] The broadcast forwarding module is used by relay nodes in each area to broadcast the relay alarm data, send the relay alarm data to the terminal alarm nodes within its coverage area, and forward it to relay nodes in other areas with path identifiers to generate diffuse alarm data.

[0020] The terminal triggering module is used to receive and deduplicate alarm data from the terminal alarm node according to the path identifier, and to determine the trigger for non-repeated alarm data based on the vibration intensity threshold. When the triggering conditions are met, an audible and visual alarm signal is generated to obtain a valid alarm triggering result.

[0021] The suppression module is used to suppress alarm output when the regional relay node does not generate relay alarm data within a preset time window.

[0022] The above-described solution of the present invention has at least the following beneficial effects:

[0023] First, by constructing a distributed alarm network consisting of earthquake monitoring nodes, regional relay nodes, and terminal alarm nodes, alarm data can be transmitted and processed collaboratively by multiple nodes within the network. Compared with the method of relying on a central server to issue unified instructions, this effectively reduces the dependence on the central node, avoids alarm delays or failures caused by link congestion or node failures, and improves the overall reliability of the system.

[0024] Secondly, by forming a multi-path propagation mechanism among regional relay nodes, the same primary alarm data can be transmitted to multiple nodes along different paths. Even if communication is blocked in underground space or some links are interrupted, data transmission can still be completed through other paths, thereby improving the success rate and stability of alarm information transmission in complex scenarios.

[0025] Furthermore, by performing path identification and receiving time difference calculation on data from different paths within a preset time window, and combining path quantity information and time interval distribution characteristics for comprehensive analysis, the system can impose multi-dimensional constraints on data from both path and time dimensions. Compared to methods that rely solely on single-point data or single-path judgment, this effectively improves the accuracy of data judgment.

[0026] Furthermore, by applying a threshold to the time difference and introducing a time interval distribution consistency constraint, the data involved in the judgment not only meets the time range condition but also conforms to the overall distribution characteristics, thereby reducing misjudgments caused by local time proximity but overall anomalies and improving the reliability of alarm results.

[0027] Furthermore, by verifying the path independence of effective alarm data combinations, the data sources involved in the judgment are dispersed in terms of node type, propagation level, and source branches, avoiding the superimposed impact of similar or repeated path data on the results, thereby further reducing the risk of false alarms.

[0028] Furthermore, by broadcasting and forwarding relay alarm data through regional relay nodes, alarm information can be rapidly disseminated to terminal nodes within the network, achieving coverage even when some communication links are blocked, thereby improving the timeliness of alarm response.

[0029] Furthermore, by using terminal alarm nodes to perform deduplication based on path identifiers and only triggering judgments on non-duplicate data, the problem of duplicate alarms caused by multi-path propagation is effectively avoided, ensuring the uniqueness and accuracy of alarm output.

[0030] Finally, by performing suppression processing when the constraints of the number of paths and time distribution are not met, the system will not trigger alarms when there is insufficient or inconsistent data, thereby effectively reducing the probability of false triggering and improving the stability and practicality of the overall alarm system in complex environments. Attached Figure Description

[0031] Figure 1 This is a flowchart of an alarm method for earthquake emergency response provided by an embodiment of the present invention. Detailed Implementation

[0032] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0033] like Figure 1 As shown, an embodiment of the present invention proposes an alarm method for earthquake emergency response, the method comprising:

[0034] A distributed alarm network consisting of earthquake monitoring nodes, regional relay nodes, and terminal alarm nodes is constructed, and an adjacency node list is established in each regional relay node to form a multi-path communication link;

[0035] When an earthquake monitoring node detects an initial seismic wave signal, it processes the initial seismic wave signal to generate primary alarm data containing a vibration intensity threshold and a time stamp, and then sends the primary alarm data to the adjacent regional relay node.

[0036] After receiving the primary alarm data, the relay nodes in each area perform statistical processing on the primary alarm data. Within a preset time window, they identify the path of the primary alarm data from different transmission paths, generate corresponding path identifiers, and calculate the reception time difference for each path to generate path quantity information and time interval distribution characteristics.

[0037] Based on the path quantity information and time interval distribution characteristics, a threshold is determined for the time difference between primary alarm data from different paths, and a consistency constraint is applied to the distribution state of the time difference based on the time interval distribution characteristics to generate effective alarm data combinations; the path independence of the effective alarm data combinations is verified to generate relay alarm data.

[0038] Each regional relay node broadcasts the relay alarm data, sending it to the terminal alarm nodes within its coverage area and forwarding it to other regional relay nodes with path identifiers, thus generating propagated alarm data.

[0039] After receiving the diffused alarm data, the terminal alarm node performs deduplication based on the path identifier and determines the trigger for non-duplicate alarm data based on the vibration intensity threshold. When the triggering condition is met, an audible and visual alarm signal is generated, and a valid alarm triggering result is obtained.

[0040] When a regional relay node fails to generate relay alarm data within a preset time window, suppression processing is performed to block alarm output.

[0041] In this embodiment of the invention, by constructing a distributed alarm network consisting of earthquake monitoring nodes, regional relay nodes, and terminal alarm nodes, earthquake monitoring data can be transmitted and processed collaboratively by multiple nodes in the network, thereby overcoming the limitations of single-point detection and single-path transmission, and improving the overall reliability and coverage of the alarm system.

[0042] Once the earthquake monitoring node detects the initial seismic wave signal, it processes the seismic wave signal to generate primary alarm data containing a vibration intensity threshold and a time stamp. This ensures that the alarm data contains both intensity and time information, providing basic data support for subsequent time-difference-based judgment and processing.

[0043] After receiving primary alarm data from different transmission paths, each relay node in the region identifies the data path and generates path identifiers within a preset time window. At the same time, it calculates the reception time difference of the data corresponding to each path, thereby obtaining information on the number of paths and the distribution characteristics of time intervals. This enables the system to not only obtain the number of paths from which the data originates, but also to grasp the time distribution of data arrival, providing a basis for subsequent multi-dimensional judgment.

[0044] During the judgment phase, threshold filtering is performed on the time difference between different paths, and consistency constraints are imposed on the time difference in combination with the time interval distribution characteristics. This ensures that the data involved in the judgment simultaneously meet the range constraints and distribution structure constraints in terms of time, thereby effectively avoiding misjudgments caused by local time proximity but overall distribution abnormalities and improving the accuracy of alarm judgment.

[0045] Based on this, by verifying the path independence of effective alarm data combinations, the data sources involved in the judgment are dispersed in terms of node type, propagation level and source branch, thereby avoiding the repeated participation of data from the same or similar paths, reducing the risk of misjudgment due to path correlation, and further improving the credibility of alarm results.

[0046] Once relay alarm data is generated, the alarm information can spread along multiple paths in the network through the broadcast and forwarding mechanism of the regional relay nodes, thereby improving the speed and coverage of alarm information propagation, and providing deduplication basis for terminal nodes by carrying path identifiers.

[0047] After receiving the propagated alarm data, the terminal alarm node performs deduplication based on the path identifier and only triggers the alarm for non-repeated data, thereby avoiding repeated alarms caused by the same event during multi-path propagation and ensuring the uniqueness and accuracy of the alarm output. At the same time, it performs trigger judgment based on the vibration intensity threshold to match the alarm trigger with the actual vibration intensity, thereby improving the effectiveness of the alarm.

[0048] When a regional relay node does not generate relay alarm data within a preset time window, the alarm output is blocked by performing suppression processing, so that the system does not trigger an alarm if the constraints of the number of paths and time distribution are not met, thereby effectively reducing the probability of false triggering.

[0049] In a preferred embodiment of the present invention, the following concepts are distinguished:

[0050] Path information: including node sequence, direction information, forwarding records, and all other path-related information;

[0051] Path structure information: The serialized identifier obtained after encoding the path information;

[0052] Path identifier: A unique index value or abbreviation corresponding to the path structure information;

[0053] Path data group: A data set with the same path structure information or that meets the merging criteria.

[0054] In a preferred embodiment of the present invention, a distributed alarm network is constructed, consisting of earthquake monitoring nodes, regional relay nodes, and terminal alarm nodes. An adjacency list is established in each regional relay node to form a multi-path communication link, including:

[0055] Earthquake monitoring nodes, regional relay nodes, and terminal alarm nodes are deployed in a distributed manner according to the preset geographical area, and each node is assigned a unique node identifier to enable identification and communication between nodes.

[0056] The neighboring node information is pre-stored in the regional relay node. By evaluating the physical distance between nodes, the communication signal strength and the historical communication stability, neighboring nodes that can communicate directly are screened and a list of neighboring nodes is established.

[0057] The node identifier, connection quality level, and communication delay level of each neighboring node are recorded in the neighboring node list, and sorted according to connection quality to form an ordered neighboring node list.

[0058] Based on the list of adjacent nodes, multiple communication paths are established between regional relay nodes. When a communication failure occurs on any path, data is forwarded by switching to the path corresponding to other adjacent nodes, thus forming a multi-path communication link.

[0059] During the network initialization phase, the list of adjacent nodes is updated periodically through interaction, and the adjacency relationship is adjusted according to the communication status to maintain the effectiveness of multi-path communication links.

[0060] In a preferred embodiment of the present invention, the initial seismic wave signal is processed to generate primary alarm data including a vibration intensity threshold and a time stamp, including:

[0061] Seismic wave signals are continuously acquired by sensors in the earthquake monitoring nodes, the raw vibration data is converted into electrical signal data, and then noise reduction and filtering are performed.

[0062] Feature extraction is performed on the filtered signal to obtain information on the change of vibration amplitude within a preset time period, and the vibration intensity level is determined based on the vibration amplitude.

[0063] According to the preset vibration intensity level classification rules, the vibration intensity level is mapped to the corresponding vibration intensity threshold range, and the corresponding threshold is selected as the vibration intensity threshold.

[0064] Read the local time of the earthquake monitoring node and write it into the data as a time identifier;

[0065] The vibration intensity threshold, time marker, and node marker are combined to form the primary alarm data.

[0066] In a preferred embodiment of the present invention, the method for setting a preset time window includes:

[0067] Based on the communication delay between nodes in a distributed alarm network, statistical analysis is performed on the data arrival time of different paths during historical data transmission to obtain the range of variation in data transmission time.

[0068] Record and sort the data transmission time of each path to determine the time distribution range;

[0069] Based on the time distribution range, select the interval covering the arrival time of the main data as the basic time range, and add a preset margin to this basic time range to adapt to communication fluctuations.

[0070] The basic time range is adjusted based on the node size and network topology to ensure that data from different paths is processed within a unified time range.

[0071] Set the adjusted time range as the preset time window and configure it in each regional relay node.

[0072] In a preferred embodiment of the present invention, deduplication is performed based on the path identifier, and non-repeating alarm data is triggered based on a vibration intensity threshold; when the triggering condition is met, an audible and visual alarm signal is generated to obtain a valid alarm triggering result, including:

[0073] After receiving the propagation alarm data, the terminal alarm node extracts the vibration intensity threshold and path identifier.

[0074] The path identifier is parsed and compared with the historical path identifiers stored locally to determine whether the current alarm data is duplicate alarm data.

[0075] When the path identifier already exists in the history, the current alarm data is determined to be duplicate data, and the most recent reception time, number of duplicate arrivals or status information in the corresponding history is updated, and no alarm output is executed;

[0076] When the path identifier does not exist in the history, the vibration intensity threshold is compared with the local preset alarm trigger threshold;

[0077] When the vibration intensity threshold meets the triggering condition, the sound and light alarm device is controlled to output an alarm signal, which emits a warning sound through the sound device and a flashing signal through the light device.

[0078] Write the current path identifier into the history record, and record the corresponding alarm time and trigger status to form a valid alarm trigger result;

[0079] When the vibration intensity threshold does not meet the triggering conditions, the current alarm data is recorded and stored, and the current processing flow ends.

[0080] In a preferred embodiment of the present invention, statistical processing is performed on the primary alarm data. Within a preset time window, path identification is performed on the primary alarm data from different transmission paths to generate corresponding path identifiers. The receiving time difference for each path is calculated to generate path quantity information and time interval distribution characteristics, including:

[0081] Based on the initial alarm data, extract the sending node identifier and time identifier to generate a set of node source information;

[0082] The sending paths are distinguished and processed according to the node source information set, and the nodes are marked according to their hierarchical position in the distributed alarm network and the number of historical forwardings, generating path structure information and corresponding path identifiers;

[0083] Based on the path structure information, primary alarm data with different path sources are grouped to generate path data groups;

[0084] Statistical processing is performed based on the number of path data groups to determine the number of different sending paths and generate path quantity information.

[0085] Within a preset time window, the time identifiers in each path data group are sorted, and an arrival time sequence is generated based on the order of the time identifiers.

[0086] Based on the arrival time series, the time identifiers of different path data groups are compared pairwise to determine the time interval relationship between the time identifiers and generate a time interval set.

[0087] Statistical processing is performed on the time interval distribution of each path data group based on the time interval set to determine the time interval distribution characteristics between each path data group.

[0088] In this embodiment of the invention, path identification and reception time difference calculation are performed on the primary alarm data. Within a preset time window, different path data are grouped, sorted, and compared pairwise. This allows for the systematic extraction of time interval relationships between path data, forming a time interval set. Further statistical processing of these time intervals yields the time interval distribution characteristics between each path data group, ensuring that time information is no longer limited to a single time difference but reflects an overall distribution structure. This processing method enables the system to simultaneously acquire path quantity information and time distribution characteristics, providing multi-dimensional data support for subsequent judgment stages. This avoids the limitations of relying solely on single-point time differences for judgment, improving the completeness and consistency of data analysis.

[0089] In a preferred embodiment of the present invention, primary alarm data with different path sources are grouped according to path structure information to generate path data groups, including:

[0090] Read the primary alarm data within the preset time window and extract the corresponding path structure information;

[0091] Based on the node sequence information, propagation direction information, and hierarchical marking information in the path structure information, the path source of the primary alarm data is compared to identify data with consistent path source characteristics.

[0092] Primary alarm data with consistent path structure information are grouped into the same data set, while data with inconsistent path structure information are divided into different data sets.

[0093] For primary alarm data with differences in path structure information but consistent propagation direction and trunk node order, the data is judged according to the preset path merging rules. When the differences meet the merging conditions, they are merged into the data set corresponding to the same path source.

[0094] Assign a corresponding path group identifier to each data set, and organize the data according to the path group identifier to generate path data groups;

[0095] The path data group is cached and stored for subsequent path count statistics and time-based sorting processing.

[0096] In a preferred embodiment of the present invention, based on path quantity information and time interval distribution characteristics, a threshold is determined for the time difference between primary alarm data from different paths, and a consistency constraint is applied to the distribution state of the time difference based on the time interval distribution characteristics to generate a valid alarm data combination; the path independence of the valid alarm data combination is verified to generate relay alarm data, including:

[0097] Based on the path quantity information and time interval distribution characteristics, the corresponding path information is extracted to generate a candidate path set;

[0098] Based on the candidate path set, the corresponding primary alarm data are aggregated and processed to extract the vibration intensity threshold and time identifier, and a candidate alarm data set is generated.

[0099] The time difference is calculated based on the time identifier in the candidate alarm data set to generate a time difference data set.

[0100] Threshold filtering is performed on the time difference data set to select data whose time difference meets the preset time difference threshold range. Consistency constraint processing is then applied to the distribution state of the time difference data set based on the time interval distribution characteristics to generate a time data group that meets the consistency constraint conditions.

[0101] Statistical processing is performed on the path information corresponding to the time data group, and data groups with a number of paths not less than the preset path number threshold are selected to generate valid alarm data combinations.

[0102] Based on the path information in the effective alarm data combination, the primary alarm data of different paths are cross-validated to confirm that the number of overlaps in the path source in terms of node type, propagation level and source branch dimension meets the preset overlap threshold condition, and the path independence result is generated.

[0103] When the path independence result meets the preset independence condition, the vibration intensity threshold in the effective alarm data combination is weighted and integrated to generate a unified vibration intensity parameter, and relay alarm data is generated in combination with the corresponding time identifier.

[0104] When the path independence result does not meet the preset independence condition, a filtering process is performed to remove data with duplicate nodes, and the time difference threshold is re-determined and consistency constraint is re-processed based on the removed data to regenerate a time data group that meets the condition.

[0105] When the number of data groups without generated paths is not less than the preset path number threshold, the generation of valid alarm data groups is blocked.

[0106] In this embodiment of the invention, a threshold is determined for the time difference between primary alarm data from different paths, and the distribution of the time difference is constrained based on the time interval distribution characteristics. This ensures that the time filtering process has both range and structural constraints, thereby selecting data combinations that meet both the threshold requirements and the overall distribution pattern in terms of time. Furthermore, the number of paths is further filtered to ensure that the number of data source paths participating in the combination meets preset conditions, thus improving the diversity of data sources. Simultaneously, path independence verification is introduced, cross-validating the node types, propagation levels, and source branches between paths. This ensures that the data participating in the judgment is dispersed along the propagation path, avoiding the influence of repeated or highly overlapping paths on the results, thereby generating more reliable relay alarm data.

[0107] In a preferred embodiment of the present invention, based on the path quantity information and time interval distribution characteristics, corresponding path information is extracted to generate a candidate path set, including:

[0108] Read the number of paths within a preset time window and determine the number of path data groups;

[0109] Read the time interval distribution characteristics corresponding to the path data group, and analyze the distribution status of each path data group in different time intervals;

[0110] Based on the number of paths, filter the path data groups that participate in alarm data transmission, and extract the corresponding path structure information, source node information, and propagation direction information;

[0111] Based on the time interval distribution characteristics, the path data groups are processed for validity identification, retaining the path data groups that meet the distribution rules and removing the path data groups whose time distribution does not meet the rules.

[0112] The filtered path information is summarized and organized according to the path source to generate a candidate path set;

[0113] Establish an index relationship for the paths in the candidate path set for subsequent time difference determination processing.

[0114] In a preferred embodiment of the present invention, the method for setting a preset time difference threshold range includes:

[0115] The arrival time data of the same event transmitted through different paths in a distributed alarm network is collected, and the time difference between the paths is extracted as sample data.

[0116] The time difference samples were sorted to determine the main distribution range;

[0117] In addition to the main distribution range, a preset margin is added to form a time range that can cover communication delay fluctuations;

[0118] Apply the time range to simulated or test data for validation to determine whether it can cover valid data and exclude outlier data.

[0119] When the verification result meets the preset requirements, the time range is determined as the preset time difference threshold range;

[0120] The time difference threshold range is updated based on the network operating status to adapt to changes in communication latency.

[0121] In a preferred embodiment of the present invention, consistency constraint processing is applied to the distribution state of the time difference data set based on the time interval distribution characteristics to generate a time data group that satisfies the consistency constraint conditions, including:

[0122] Read the time difference data set and the corresponding path source information;

[0123] The time difference data is categorized according to preset time intervals to obtain interval distribution results;

[0124] Based on the characteristics of time interval distribution, the interval distribution of time difference data is judged. When the time difference is concentrated in adjacent intervals or the same interval, it is determined that the concentration condition is met.

[0125] The distribution of time difference across multiple intervals is judged to be continuous. When the interval distribution is continuous and there are no discontinuous segments, it is judged to meet the continuity condition.

[0126] Identify time difference data that deviate from the main distribution range and mark them as data that do not meet the consistency condition;

[0127] The path data corresponding to the time difference data that meet the conditions of concentration and continuity are combined to generate time data groups;

[0128] Data that does not meet the consistency criteria will not be processed in the current timeframe and will be adjusted in the subsequent time interval or processed in the next round.

[0129] In a preferred embodiment of the present invention, the method for setting a preset path quantity threshold includes:

[0130] Based on the number of neighboring nodes of a regional relay node and the number of communication paths that can be formed, a statistical analysis is performed on the scale of path sources.

[0131] By combining historical operational data, we can statistically analyze the distribution of the number of paths that can reach the regional relay nodes under the same event and determine the reference range.

[0132] Based on the system's false alarm control requirements and alarm timeliness requirements, the number of paths is selected from the reference range as the lower limit for judgment;

[0133] Test and verify the number of selected paths, and evaluate their alarm effect under different network conditions and event conditions;

[0134] When the verification results meet the requirements for false alarm control and alarm response, the number of paths is set as the preset path number threshold.

[0135] Based on changes in network structure and operational data, the path count threshold is updated to maintain consistency with the current network state.

[0136] In a preferred embodiment of the present invention, the transmission path is differentiated based on the node source information set, and marked according to the node's hierarchical position in the distributed alarm network and its historical forwarding count, generating path structure information and corresponding path identifiers, including:

[0137] Based on the sending node identifier in the node source information set, extract the source node and its superior forwarding node corresponding to each primary alarm data, and generate node connection relationship data.

[0138] Based on the node connection relationship data, the propagation path of each primary alarm data is restored to form a path sequence in which multiple nodes are connected in sequence, and a path topology result is generated.

[0139] Based on the path topology results, the order of nodes in the path is marked, the positional relationship of each node in the path is recorded, and the node order marking results are generated.

[0140] Based on the node connection relationship data, backtracking detection is performed on the nodes in the path to determine whether there are duplicate nodes in the path and generate path loop determination results;

[0141] Based on the path loop determination results, the paths with duplicate nodes are truncated to generate a loop-free path structure;

[0142] The path propagation direction is determined based on the acyclic path structure to identify the entry and diffusion directions of the path, and a direction marking result is generated.

[0143] Based on the node sequence marking results, direction marking results, and the node's hierarchical position in the distributed alarm network, the path is structurally encoded, and path structure information is generated by combining the historical forwarding counts of each node.

[0144] In this embodiment of the invention, by parsing the node source information, extracting the source node and its superior forwarding nodes, and constructing node connection relationship data, the propagation paths of each primary alarm data can be restored into an ordered path sequence. Based on this, by marking the node order in the path and backtracking to detect node repetition, loops in the path can be identified and truncated, thus forming a loop-free path structure and avoiding interference from path loops to subsequent analysis. Simultaneously, by combining the determination of the path propagation direction with information on node hierarchical position and historical forwarding counts, the path is structurally encoded, making different paths distinguishable at the encoding level. Finally, the path structure information is used to distinguish paths with different propagation directions and node sequences, achieving independent division of the transmission path and providing an accurate basis for subsequent path quantity statistics and path independence verification.

[0145] In a preferred embodiment of the present invention, the path containing duplicate nodes is truncated based on the path loop determination result to generate a loop-free path structure, including:

[0146] Read the path loop determination results and extract the paths with duplicate nodes;

[0147] The node sequence in the path is examined according to the data propagation order to determine the first and second occurrence positions of the duplicate nodes in the node sequence;

[0148] When the same node appears twice or more in the path, the node segment between the first occurrence and the second occurrence is identified as a loop segment and marked.

[0149] Based on the position of the loop segment in the path, the path is truncated, retaining the node segment from the starting node to the first occurrence of the repeating node, and the node segment after the recurrence of the repeating node, in order to remove the closed propagation part.

[0150] When there are multiple duplicate nodes in the path, the truncation process is performed in the order in which the nodes appear, and the node sequence is updated after each truncation.

[0151] After verifying the truncated path and confirming that there are no duplicate nodes in the node sequence, it is determined to be an acyclic path structure.

[0152] The acyclic path structure is associated with and stored with the path source information for later processing.

[0153] In a preferred embodiment of the present invention, the path propagation direction is determined based on the acyclic path structure to identify the entry and diffusion directions of the path, and a direction marking result is generated, including:

[0154] Read the node sequence and the connection relationships between adjacent nodes in an acyclic path structure;

[0155] Based on the information of the first node, last node, and source node of the path, determine the direction of entry of the path into the relay node of the current area;

[0156] Based on the forwarding relationship of nodes in the path, the direction of alarm data propagation from the current node to subsequent nodes is determined, thus obtaining the diffusion direction;

[0157] Based on the connection relationship information of the previous hop node, determine the connection link information corresponding to the incoming direction;

[0158] Based on the connection information of the next-hop node, determine the propagation link information corresponding to the diffusion direction;

[0159] The entry direction information and the diffusion direction information are combined to form the direction marking result;

[0160] The direction marking results are associated with and stored in the acyclic path structure for use in path encoding processing.

[0161] In a preferred embodiment of the present invention, the path is structurally encoded based on the node sequence marking result, direction marking result, and the node's hierarchical position in the distributed alarm network, and path structure information is generated by combining the historical forwarding count of each node, including:

[0162] Read the node sequence marking results, extract the propagation order of each node in the path, and use it as the basis for the path encoding order;

[0163] Read the direction marking results, extract the entry direction and diffusion direction of the path, and use them as the direction basis for path encoding;

[0164] Read the hierarchical position of each node in the distributed alarm network, determine the network hierarchical position of the node, and use it as the hierarchical basis for path coding;

[0165] According to the preset encoding rules, the node sequence information, direction information and hierarchy information are combined and processed to generate the initial encoding result of the path;

[0166] Read the historical forwarding count of each node and classify and label the forwarding frequency of the nodes according to the preset classification rules;

[0167] Write the node forwarding frequency marker into the corresponding node position in the initial coding result so that the path coding contains structural information and forwarding feature information;

[0168] The path codes are organized to generate path structure information arranged in the order of node propagation;

[0169] The path structure information is associated with and stored with the corresponding primary alarm data for subsequent path grouping, path independence verification, and duplicate path identification processing.

[0170] In a preferred embodiment of the present invention, the preset encoding rules include:

[0171] Each node is encoded sequentially according to its propagation order in the path.

[0172] Each node is represented in the form of a triple, which includes a node sequence identifier, a direction identifier, and a hierarchy identifier.

[0173] in:

[0174] The node sequence identifier is used to indicate the position number of a node in the path;

[0175] The direction identifier is used to indicate the direction of propagation of the path at the node. The direction identifier can use binary encoding to represent the direction of entry and the direction of spread.

[0176] Hierarchical identifiers are used to indicate the hierarchical position of a node in a distributed alarm network;

[0177] The triples corresponding to each node are concatenated according to the path propagation order to generate the initial encoding result of the path.

[0178] In a preferred embodiment of the present invention, the preset grading rules include:

[0179] Based on the number of times a node forwards its data within a preset time range, nodes are divided into different forwarding frequency levels.

[0180] in:

[0181] When the number of historical forwards is less than the first threshold, it is marked as a low-frequency node;

[0182] When the number of historical forwardings is between the first threshold and the second threshold, it is marked as a mid-frequency node;

[0183] When the number of historical forwards exceeds the second threshold, it is marked as a high-frequency node;

[0184] Each frequency level is assigned a corresponding frequency identifier, which is then written into the corresponding node position in the path encoding.

[0185] In a preferred embodiment of the present invention, statistical processing is performed on the time interval distribution of each path data group based on the time interval set to determine the time interval distribution characteristics between each path data group, including:

[0186] The time intervals in the time interval set are classified and divided according to the preset time interval range to generate a time interval range set;

[0187] Based on the set of time interval intervals, the time intervals in each path data group are mapped to the corresponding time interval intervals, and the interval mapping results are generated.

[0188] Based on the interval mapping results, the number of time intervals for each path data group within each time interval is statistically processed to generate interval counting results;

[0189] Based on the interval counting results, the distribution of each path data group in different time intervals is sorted out and processed to generate a time interval distribution sequence.

[0190] Based on the time interval distribution sequence, statistical processing is performed on the occurrence of each path data group in multiple time intervals to determine the frequency of occurrence of each path data group in different time intervals and generate interval distribution results.

[0191] Based on the interval distribution results, the continuity of the distribution of each path data group in multiple time intervals is determined and processed to generate a continuous time interval distribution result.

[0192] The time interval distribution characteristics are generated by comprehensively summarizing and processing the interval counting results, interval distribution results, and continuous time interval distribution results.

[0193] In this embodiment of the invention, by dividing the time intervals in the time interval set into intervals and mapping the time intervals in each path data group to the corresponding intervals, discrete time difference data is uniformly converted into structured interval data. Based on this, by statistically analyzing the number of time intervals within each interval and generating interval counting results, the distribution of different path data in each time interval can be quantitatively expressed. Furthermore, by organizing and generating a time interval distribution sequence and analyzing the frequency of occurrence and distribution continuity of each interval, the distribution of time intervals not only reflects quantitative characteristics but also the continuous relationship between intervals. By comprehensively summarizing the interval counting results, interval distribution results, and continuous distribution results, an overall time interval distribution characteristic is formed, thereby transforming time information from a single numerical relationship into a multi-dimensional distribution structure, providing a more complete data foundation for subsequent consistency constraints.

[0194] In a preferred embodiment of the present invention, the method for setting the preset time interval includes:

[0195] Collect time interval data generated by the distributed alarm network during historical alarm events, simulated test events, or joint debugging tests, and extract the arrival time difference between different paths as sample data;

[0196] The sample data was sorted to determine the main and abnormal distribution ranges of the time intervals.

[0197] Based on the distribution range, select a continuous time period covering the main time intervals as the initial interval range, and arrange each interval continuously in chronological order.

[0198] Based on the distribution density of time intervals, set corresponding interval widths for different intervals to ensure that the interval divisions can reflect the characteristics of time interval changes.

[0199] The divided time intervals are applied to the sample data for validation processing to determine whether the interval division can distinguish between normal data and abnormal data.

[0200] When the verification result meets the preset requirements, the interval is determined as the preset time interval.

[0201] The time intervals are updated based on the network operating status to adapt to changes in the time interval distribution.

[0202] In a preferred embodiment of the present invention, interval mapping processing is performed on the time intervals in each path data group according to the time interval interval set, and each time interval is assigned to the corresponding time interval interval to generate an interval mapping result, including:

[0203] Read the path data group and the corresponding time interval set within the preset time window, and extract the value of each time interval and the path source information;

[0204] Read the set of time intervals and sort them in order of interval range;

[0205] The time intervals are matched with the interval set, and the time intervals are assigned to the corresponding time interval intervals.

[0206] When the time interval is located at the interval boundary, its interval is determined according to preset rules;

[0207] Record the path data group identifier, interval identifier, and position within the interval corresponding to each time interval to form a mapping record;

[0208] Summarize the mapping records of the same path data group to generate interval mapping results;

[0209] The interval mapping results are associated with and stored with the path data group.

[0210] In a preferred embodiment of the present invention, based on the interval counting results, the distribution of each path data group within different time intervals is processed to generate a time interval distribution sequence, including:

[0211] Read the count results of each path data group in each time interval;

[0212] The count data of each interval are arranged in order of time interval to form an ordered distribution record;

[0213] For intervals with time intervals, record their distribution and corresponding quantity; for intervals without time intervals, record them as empty.

[0214] The distribution status and quantity information of each interval are continuously organized to form an interval distribution sequence;

[0215] The interval distribution sequence is processed in a unified format so that the data groups of each path form a time interval distribution sequence with a consistent structure;

[0216] The time interval distribution sequence is stored as the time distribution representation of the path data group.

[0217] In a preferred embodiment of the present invention, based on the interval distribution results, the continuity of the distribution of each path data group within multiple time intervals is determined, and a continuous time interval distribution result is generated, including:

[0218] Read the interval distribution results of the path data group, and extract the occurrence and order of each interval;

[0219] Examine the distribution of each interval in chronological order to determine whether there is a continuous distribution between adjacent intervals;

[0220] When the interval distribution is uninterrupted within a continuous interval, it is determined to be a continuous distribution state;

[0221] When there are discontinuities in the interval distribution, determine the number and range of discontinuous intervals;

[0222] Based on the judgment results, the distribution state of the path data group is divided into continuous distribution state, weakly continuous distribution state, or discrete distribution state.

[0223] Generate corresponding continuous markers and form a continuous distribution result of time intervals;

[0224] The results of the continuous distribution of time intervals are associated with the path data group and stored together.

[0225] In a preferred embodiment of the present invention, the time interval distribution characteristics are generated by comprehensively summarizing the interval counting results, interval distribution results, and continuous time interval distribution results, including:

[0226] Read the interval count results, interval distribution results, and continuous time interval distribution results corresponding to the path data group, and perform matching processing;

[0227] Determine the concentrated distribution interval of the time interval based on the interval counting results;

[0228] The distribution range of time intervals and the positional relationship between intervals are determined based on the interval distribution results;

[0229] The continuity characteristics of the distribution are determined based on the results of the continuous distribution over time intervals;

[0230] The quantitative characteristics, location characteristics, and continuity characteristics are comprehensively organized to generate a time interval distribution description of the path data group;

[0231] Based on the time interval distribution description, the path data group is divided into a concentrated continuous distribution type, a diffuse distribution type, or a discrete distribution type;

[0232] The distribution types of each path data group are summarized to generate time interval distribution characteristics, which are then used as input data for consistency constraint processing.

[0233] In a preferred embodiment of the present invention, based on the path information in the effective alarm data combination, cross-validation processing is performed on the primary alarm data of different paths to confirm that the number of overlaps in the path source in terms of node type, propagation level, and source branch dimension meets the preset overlap threshold condition, and a path independence result is generated, including:

[0234] Based on the path information in the valid alarm data combination, extract the node sequence and propagation direction information corresponding to each path to generate a path node set.

[0235] Based on the set of path nodes, the nodes between different paths are compared one by one to determine the common nodes between the paths and generate the node overlap result.

[0236] Based on the node overlap results, the node positions in the path are classified and processed. The independence of the starting node, relay node and the ending node are analyzed separately to generate node type independence results.

[0237] The path length result is generated by statistically analyzing the propagation hop count in the path based on the path node set.

[0238] Based on the path length results, different paths are compared to determine the differences in propagation levels between paths and generate propagation level difference results.

[0239] The entry directions of the paths are compared based on the path information to determine whether the paths originate from the same source branch, and a source branch determination result is generated.

[0240] The results are comprehensively verified based on the results of node type independence, propagation level difference, and source branch determination. When the number of overlaps in the three dimensions of node type, propagation level, and source branch is less than the preset overlap threshold, a path independence result that meets the preset independence condition is generated; otherwise, a path independence result that does not meet the preset independence condition is generated.

[0241] In this embodiment of the invention, by extracting the set of path nodes from the valid alarm data combination and comparing the nodes of different paths one by one, the common nodes between paths can be identified, thereby determining the overlap relationship between paths. Based on this, by classifying the node positions and performing independence analysis on the starting node, relay node, and terminal node respectively, the degree of overlap of paths in different node type dimensions can be distinguished. Further, by combining path length statistics and propagation level difference analysis, the differences in propagation levels of different paths are reflected. Simultaneously, by comparing the path entry direction, it is determined whether the paths originate from the same diffusion branch, thereby distinguishing them in the source dimension. Finally, by comprehensively verifying the overlap of node type, propagation level, and source branch dimensions, it is possible to determine whether paths possess independence, thereby avoiding paths with similar sources or structures from repeatedly participating in the judgment, and improving the reliability of relay alarm data.

[0242] In a preferred embodiment of the present invention, based on the path information in the effective alarm data combination, the node sequence and propagation direction information corresponding to each path are extracted to generate a path node set, including:

[0243] Read the path information from the valid alarm data combination, and extract the path structure information, source node identifier and forwarding record information;

[0244] The node identifiers are parsed based on the path structure information, and a node sequence is formed according to the propagation order.

[0245] Based on the position of the node in the path, the nodes are divided into starting nodes, relay nodes and ending nodes to form a node sequence description;

[0246] Read the direction marker results corresponding to the path and extract the entry direction information and diffusion direction information;

[0247] The node sequence description is combined with the direction information to form a path description unit;

[0248] Summarize the description units of each path to generate a set of path nodes;

[0249] The path node set is associated with and stored together with the valid alarm data.

[0250] In a preferred embodiment of the present invention, the nodes of different paths are compared one by one according to the path node set to determine the common nodes between the paths and generate a node overlap result, including:

[0251] Read the node sequence of each path and establish the pairing relationship between paths;

[0252] For each pair of paths, the node identifiers are compared item by item to identify identical node identifiers;

[0253] Nodes with the same identifier are identified as common nodes, and their positions in each path are recorded.

[0254] Summarize and record multiple common nodes in the same path pair;

[0255] Generate records of overlapping nodes based on the number and location distribution of common nodes;

[0256] Based on the overlapping records of nodes, a node overlap result is generated;

[0257] The results of node overlap are associated with the path pairing and stored.

[0258] In a preferred embodiment of the present invention, the node positions in the path are classified according to the node overlap results, and the independence of the starting node, relay node, and terminal node are analyzed separately to generate node type independence results, including:

[0259] Read the node overlap results and extract the common nodes and their positions in the path;

[0260] Based on the position of the nodes in the path, common nodes are divided into overlapping starting nodes, overlapping relay nodes, and overlapping ending nodes.

[0261] Count the number of overlaps for each path pair across different node types;

[0262] Based on the overlap of starting nodes, determine whether the starting sources of the paths are consistent;

[0263] Based on the overlap of relay nodes, determine whether the path propagation process passes through the same nodes;

[0264] Based on the overlap of the end nodes, determine whether there is a convergence relationship at the end of the path;

[0265] The above analysis results are organized to generate node type independence results;

[0266] Use the node type independence result as input for subsequent independence determination.

[0267] In a preferred embodiment of the present invention, different paths are compared based on the path length results to determine the differences in propagation levels between paths, and a propagation level difference result is generated, including:

[0268] Read the propagation hop count information for each path;

[0269] The propagation hop counts of different paths are compared pairwise to determine the differences in hop counts between paths;

[0270] Determine the differences in propagation levels of the paths based on the differences in hop count;

[0271] The differences in the propagation levels of each path pair are classified and organized.

[0272] Generate propagation hierarchy difference results based on the classification results;

[0273] The propagation level difference results are associated and stored with path pairing information.

[0274] In a preferred embodiment of the present invention, the entry directions of the paths are compared based on the path information to determine whether the paths originate from the same source branch, and a source branch determination result is generated, including:

[0275] Read the path information and direction marker results, and extract the entry direction information;

[0276] Identify the previous hop node or source branch of the path based on the direction of entry;

[0277] Compare the entry directions of different paths to determine their source relationships;

[0278] When paths originate from the same node or the same branch, they are considered to be of the same origin.

[0279] When paths originate from different nodes or different branches, they are determined to be paths from different sources;

[0280] The source relationships between paths are classified and organized to generate source branch determination results;

[0281] Use the source branch determination result as input for independence verification.

[0282] In a preferred embodiment of the present invention, the method for setting a preset overlap threshold includes:

[0283] Collect path propagation data from historical alarm events and test data, and extract the overlap of paths in terms of node type, propagation level, and source branch.

[0284] Statistical analysis was conducted on path overlap in different scenarios to determine the overlap characteristics between valid alarms and false alarms;

[0285] Based on the statistical results, the range of allowed node overlap is determined in terms of node type.

[0286] Determine the permissible range of differences in propagation levels at the propagation level dimension;

[0287] Determine the allowed overlap of source branches at the source branch level;

[0288] The overlap range of each dimension is combined to determine the preset overlap threshold;

[0289] The overlap threshold was applied to the test data for verification to confirm its effectiveness in path filtering;

[0290] The verified overlap threshold is used for system operation and updated based on the operation data.

[0291] In a preferred embodiment of the present invention, the vibration intensity thresholds in the valid alarm data combination are weighted and integrated to generate a unified vibration intensity parameter, including:

[0292] Based on the combination of valid alarm data, extract the vibration intensity threshold, path information and time identifier corresponding to each primary alarm data;

[0293] The propagation hop count of each path is statistically processed based on the path information to generate path length marking results;

[0294] The node hierarchical positions of each path are parsed based on the path information to generate hierarchical position marking results;

[0295] The arrival times of each path data are sorted according to the time identifier to generate a time sequence label result;

[0296] Based on the path length marking results, the path propagation hop count is divided into intervals, and the path length weight is assigned to the corresponding vibration intensity threshold according to the interval where the path propagation hop count is located. The path length weight is negatively correlated with the propagation hop count.

[0297] Based on the hierarchical location marking results, the node hierarchical location is divided into intervals, and the corresponding vibration intensity threshold is assigned a hierarchical weight according to the interval where the node hierarchical location is located. The hierarchical weight has a preset functional relationship with the node hierarchical depth.

[0298] Based on the time sequence marking results, the arrival time order of each path data is sorted, and time weights are assigned to the corresponding vibration intensity thresholds according to the sorting sequence number, wherein the time weights decrease with the arrival time order.

[0299] The results of path length weight, hierarchy weight, and time weight are combined and processed, and the weight values ​​are superimposed to generate a comprehensive weight result.

[0300] The intensity data set is integrated and processed based on the comprehensive weighting results. Each vibration intensity threshold is weighted and accumulated with its corresponding comprehensive weight, and the accumulated result is normalized to generate a unified vibration intensity parameter.

[0301] In this embodiment of the invention, vibration intensity thresholds, path information, and time identifiers are extracted from effective alarm data combinations. These are then combined with multi-dimensional labeling based on path propagation hop count, node hierarchical position, and data arrival time sequence, providing a structured description of the vibration intensity corresponding to different paths. Furthermore, by segmenting the path length, hierarchical position, and time sequence and assigning corresponding weights, differences in propagation distance, network hierarchical position, and time sequence among different paths are reflected in the weight allocation. Further, by combining various weights, a comprehensive weight result is generated. Based on this comprehensive weight, each vibration intensity threshold is weighted, accumulated, and normalized, ensuring that the final unified vibration intensity parameter comprehensively reflects the overall situation of multi-path data. This avoids bias from data from a single path or a single time point, improving the stability of vibration intensity representation in relay alarm data.

[0302] In a preferred embodiment of the present invention, the propagation hop count of each path is statistically processed based on the path information to generate a path length marking result, including:

[0303] Read the path information corresponding to each path in the valid alarm data combination, and extract the node sequence, forwarding record information and node connection order information of each path;

[0304] According to the propagation order of alarm data in the path, the node connection relationship in each path is unfolded in turn, and the number of node forwardings traversed by each path from the starting node to the current node is determined.

[0305] One data transmission between two adjacent nodes in the path is recorded as one propagation jump, and the number of propagation jumps is accumulated segment by segment from the starting node to the ending node of the path to obtain the propagation jump number for each path;

[0306] When the path contains a loop-free path structure that has been truncated, the propagation hop count is based on the truncated valid node sequence to avoid duplicate nodes or loop nodes affecting the statistical results.

[0307] The propagation hop count of each path is associated with the path identifier and recorded, and then classified according to the preset classification rules, marking the corresponding paths as short paths, medium paths or long paths respectively.

[0308] Based on the classification results, a corresponding path length label is generated for each path, and the path length label is used as the input for subsequent path length weight allocation processing.

[0309] The path length marker result is bound and stored with the corresponding vibration intensity threshold, time identifier and path information, so that it can be called when generating unified vibration intensity parameters.

[0310] In a preferred embodiment of the present invention, the node hierarchical positions of each path are parsed based on the path information to generate hierarchical position marking results, including:

[0311] Read the path information corresponding to each path, and extract the node identifier sequence contained in each path and the network role information of each node in the distributed alarm network;

[0312] Based on the pre-defined network roles of the nodes, each node is divided into earthquake monitoring nodes, regional relay nodes, and terminal alarm nodes, and the corresponding propagation level is determined by combining the sequential position of the nodes in the path.

[0313] The node located at the beginning of the path and responsible for generating primary alarm data is resolved to be a starting-level node.

[0314] Nodes located in the middle of the path and responsible for receiving, judging, broadcasting, or forwarding are resolved as relay-level nodes.

[0315] The node located at the end of the path and responsible for alarm triggering is resolved as a terminal-level node;

[0316] After completing the node role classification, the node hierarchy depth is further refined by combining the relative position of the node in the path to determine whether it belongs to the front-end, middle-end, or back-end hierarchy.

[0317] Organize the hierarchical analysis results of each node in the same path according to the propagation order, and extract the hierarchical position features used to characterize the overall structure of the path to form the hierarchical position description results of the corresponding path.

[0318] Based on the hierarchical location description results, each path is assigned a corresponding hierarchical location label to generate hierarchical location label results, which are then used as the input for subsequent hierarchical weight allocation processing.

[0319] In a preferred embodiment of the present invention, the arrival times of each path data are sorted according to the time identifier to generate a time sequence marking result, including:

[0320] Read the time identifiers corresponding to each path data in the valid alarm data combination, and extract the time information when each path data arrives at the current area relay node or participates in the judgment and processing;

[0321] The time identifiers are converted to a unified format so that the arrival times of data from different paths are represented based on the same time base;

[0322] Sort the arrival times of the path data in chronological order, arranging the path data that arrives first at the front and the subsequent arriving path data in sequence behind;

[0323] When the arrival times of two or more path data are the same, or the time difference is less than the preset minimum discrimination granularity, perform sequential subdivision by combining path identifiers, source node priorities, or propagation hop counts;

[0324] Assign sequential numbers to the sorted path data in sequence, so that each path data obtains a corresponding sorting serial number;

[0325] According to the sorting serial number, assign a pre-arrival mark, an in-order arrival mark, or a post-arrival mark to each path data respectively to generate a time sequence marking result;

[0326] Associate and store the time sequence marking result with the corresponding path information and vibration intensity threshold for subsequent time weight assignment processing to call.

[0327] In a preferred embodiment of the present invention, the path length weight can be determined as follows:

[0328] When the propagation hop count n ≤ 2, the weight is 1.0;

[0329] When 2 < n ≤ 5, the weight is 0.8;

[0330] When n > 5, the weight is 0.6;

[0331] Or in the form of a function:

[0332] w1 = 1 / (1 + α×n)

[0333] Where α is the attenuation coefficient.

[0334] In a preferred embodiment of the present invention, the hierarchical weight can be determined as follows:

[0335] When the node level is the core layer or the upper layer node, the weight is 1.0;

[0336] When the node level is the middle layer, the weight is 0.8; ​​​​​​​​​​​​​​

[0342] Sort by arrival time, with the first position having a weight of 1.0;

[0343] The second digit is 0.9;

[0344] The third digit is 0.8;

[0345] Alternatively, a function can be used:

[0346] w3=1 / (1+γ×k)

[0347] Where k is the sorting number and γ is the attenuation coefficient.

[0348] In a preferred embodiment of the present invention, the path length weight result, the level weight result, and the time weight result are combined and processed to generate a comprehensive weight result by superimposing the weight values.

[0349] Read the path length weight result, level weight result, and time weight result corresponding to each path, and match them according to the path correspondence to form the weight data group of each path;

[0350] The integrity of the weight data group for each path is checked, and the missing weight values ​​are assigned a basic weight value according to the preset completion rules. The preset completion rules include completion based on existing weight statistics or completion based on preset default weights. For example, when a certain path is missing a certain type of weight value, the missing weight is completed according to the average value of the same type of weight values ​​calculated in the current time window.

[0351] Based on the weighted data sets of each path, the path length weight value, the level weight value, and the time weight value are superimposed and calculated to generate the total weight value corresponding to each path.

[0352] A comprehensive weight result is generated based on the total weight value of each path;

[0353] The comprehensive weighting results are correlated with the corresponding vibration intensity threshold, path information, and time marker to form a comprehensive weighting data set.

[0354] Embodiments of the present invention also provide an alarm system for earthquake emergency response, the system comprising:

[0355] The network construction module is used to build a distributed alarm network consisting of earthquake monitoring nodes, regional relay nodes, and terminal alarm nodes.

[0356] The primary alarm generation module is used to process the initial seismic wave signal when the earthquake monitoring node detects the initial seismic wave signal, generate primary alarm data containing the vibration intensity threshold and time identifier, and send the primary alarm data to the adjacent regional relay node.

[0357] The statistical processing module is used to perform statistical processing on the primary alarm data after the relay nodes in each area receive the primary alarm data. Within a preset time window, it identifies the path of the primary alarm data from different transmission paths, generates the corresponding path identifier, calculates the reception time difference for each path, and generates path quantity information and time interval distribution characteristics.

[0358] The judgment generation module is used to determine the threshold of the time difference between primary alarm data from different paths based on the path quantity information and time interval distribution characteristics, and to impose consistency constraints on the distribution state of the time difference based on the time interval distribution characteristics to generate valid alarm data combinations; and to perform path independence verification on the valid alarm data combinations to generate relay alarm data.

[0359] The broadcast forwarding module is used by relay nodes in each area to broadcast the relay alarm data, send the relay alarm data to the terminal alarm nodes within its coverage area, and forward it to relay nodes in other areas with path identifiers to generate diffuse alarm data.

[0360] The terminal triggering module is used to receive and deduplicate alarm data from the terminal alarm node according to the path identifier, and to determine the trigger for non-repeated alarm data based on the vibration intensity threshold. When the triggering conditions are met, an audible and visual alarm signal is generated to obtain a valid alarm triggering result.

[0361] The suppression module is used to suppress alarm output when the regional relay node does not generate relay alarm data within a preset time window.

[0362] It should be noted that this system is a system corresponding to the above method. All implementation methods in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0363] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0364] Embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0365] The above are preferred embodiments of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. An alarm method for earthquake emergency response, characterized in that, The method includes: Construct a distributed alarm network consisting of earthquake monitoring nodes, regional relay nodes, and terminal alarm nodes; When an earthquake monitoring node detects an initial seismic wave signal, it processes the signal to generate primary alarm data containing a vibration intensity threshold, node identifier, and time identifier. This primary alarm data is then sent to neighboring regional relay nodes. The step of obtaining the vibration intensity threshold includes: continuously acquiring seismic wave signals using sensors in the earthquake monitoring node; converting the raw vibration data into electrical signal data; and performing noise reduction and filtering; extracting features from the filtered signal to obtain vibration amplitude variation information within a preset time period; and determining the vibration intensity level based on the vibration amplitude; mapping the vibration intensity level to the corresponding vibration intensity threshold range according to a preset vibration intensity level classification rule; and selecting the corresponding threshold as the vibration intensity threshold. The step of obtaining the time identifier includes: reading the local time of the earthquake monitoring node and writing it into the data as a time identifier. After receiving primary alarm data, each relay node in each area extracts the sending node identifier and time identifier from the primary alarm data to generate a node source information set. Based on the node source information set, the transmission paths are differentiated and processed, and then marked according to the node's hierarchical position in the distributed alarm network and its historical forwarding count, generating path structure information and corresponding path identifiers. Primary alarm data from different path sources are grouped based on the path structure information to generate path data groups. The number of path data groups is statistically processed to determine the number of different transmission paths, generating path quantity information. Within a preset time window, the time identifiers in each path data group are sorted, and an arrival time sequence is generated based on the order of the time identifiers. The time identifiers between different path data groups are compared pairwise based on the arrival time sequence to determine the time interval relationship between the time identifiers, generating a time interval set. The time interval distribution of each path data group is statistically processed based on the time interval set to determine the time interval distribution characteristics between each path data group. Based on the path quantity information and time interval distribution characteristics, a threshold is determined for the time difference between primary alarm data from different paths, and a consistency constraint is applied to the distribution state of the time difference based on the time interval distribution characteristics to generate effective alarm data combinations; the path independence of the effective alarm data combinations is verified to generate relay alarm data. Each regional relay node broadcasts the relay alarm data, sending it to the terminal alarm nodes within its coverage area and forwarding it to other regional relay nodes with path identifiers, thus generating propagated alarm data. After receiving the diffused alarm data, the terminal alarm node performs deduplication based on the path identifier and determines the trigger for non-duplicate alarm data based on the vibration intensity threshold. When the triggering condition is met, an audible and visual alarm signal is generated, and a valid alarm triggering result is obtained. When a regional relay node fails to generate relay alarm data within a preset time window, suppression processing is performed to block alarm output.

2. The alarm method for earthquake emergency response according to claim 1, characterized in that, Based on the number of paths and the distribution characteristics of time intervals, a threshold is determined for the time difference between primary alarm data from different paths. Consistency constraints are then applied to the distribution of these time differences based on the time interval distribution characteristics to generate valid alarm data combinations. Path independence is verified on these valid alarm data combinations to generate relay alarm data, including: The system reads the number of paths within a preset time window and determines the number of path data groups. It then reads the time interval distribution characteristics corresponding to each path data group and analyzes the distribution status of each path data group within different time intervals. Based on the number of paths, it filters the path data groups participating in alarm data transmission and extracts the corresponding path information, including path structure information, source node information, and propagation direction information. Based on the time interval distribution characteristics, it performs validity identification processing on the path data groups, retaining those that meet the distribution rules and removing those whose time distribution does not conform to the rules. Finally, it summarizes the filtered path information and organizes it according to the path source to generate a candidate path set. Based on the candidate path set, the corresponding primary alarm data are aggregated and processed to extract the vibration intensity threshold and time identifier, and a candidate alarm data set is generated. The time difference is calculated based on the time identifier in the candidate alarm data set to generate a time difference data set. Threshold filtering is performed on the time difference data set to select data whose time difference meets the preset time difference threshold range. Consistency constraint processing is then applied to the distribution state of the time difference data set based on the time interval distribution characteristics to generate a time data group that meets the consistency constraint conditions. Statistical processing is performed on the path information corresponding to the time data group, and data groups with a number of paths not less than the preset path number threshold are selected to generate valid alarm data combinations. Based on the path information in the effective alarm data combination, the primary alarm data of different paths are cross-validated to confirm that the number of overlaps in the path source in terms of node type, propagation level and source branch dimension meets the preset overlap threshold condition, and the path independence result is generated. When the path independence result meets the preset independence condition, the vibration intensity threshold in the effective alarm data combination is weighted and integrated to generate a unified vibration intensity parameter, and relay alarm data is generated in combination with the corresponding time identifier. When the path independence result does not meet the preset independence condition, a filtering process is performed to remove data with duplicate nodes, and the time difference threshold is re-determined and consistency constraint is re-processed based on the removed data to regenerate a time data group that meets the condition. When the number of data groups without generated paths is not less than the preset path number threshold, the generation of valid alarm data groups is blocked.

3. The alarm method for earthquake emergency response according to claim 1, characterized in that, The transmission paths are differentiated based on the node source information set, and then marked according to the node's hierarchical position in the distributed alarm network and its historical forwarding count to generate path structure information and corresponding path identifiers, including: Based on the sending node identifier in the node source information set, extract the source node and its superior forwarding node corresponding to each primary alarm data, and generate node connection relationship data. Based on the node connection relationship data, the propagation path of each primary alarm data is restored to form a path sequence in which multiple nodes are connected in sequence, and a path topology result is generated. Based on the path topology results, the order of nodes in the path is marked, the positional relationship of each node in the path is recorded, and the node order marking results are generated. Based on the node connection relationship data, backtracking detection is performed on the nodes in the path to determine whether there are duplicate nodes in the path and generate path loop determination results; Based on the path loop determination results, the paths with duplicate nodes are truncated to generate a loop-free path structure; The path propagation direction is determined based on the acyclic path structure to identify the entry and diffusion directions of the path, and a direction marking result is generated. Based on the node sequence marking results, direction marking results, and the node's hierarchical position in the distributed alarm network, the path is structurally encoded, and path structure information is generated by combining the historical forwarding counts of each node.

4. The alarm method for earthquake emergency response according to claim 1, characterized in that, Statistical processing is performed on the time interval distribution of each path data group based on the time interval set to determine the time interval distribution characteristics between each path data group, including: The time intervals in the time interval set are classified and divided according to the preset time interval range to generate a time interval range set; Based on the set of time interval intervals, the time intervals in each path data group are mapped to the corresponding time interval intervals, and the interval mapping results are generated. Based on the interval mapping results, the number of time intervals for each path data group within each time interval is statistically processed to generate interval counting results; Based on the interval counting results, the distribution of each path data group in different time intervals is sorted out and processed to generate a time interval distribution sequence. Based on the time interval distribution sequence, statistical processing is performed on the occurrence of each path data group in multiple time intervals to determine the frequency of occurrence of each path data group in different time intervals and generate interval distribution results. Based on the interval distribution results, the continuity of the distribution of each path data group in multiple time intervals is determined and processed to generate a continuous time interval distribution result. The time interval distribution characteristics are generated by comprehensively summarizing and processing the interval counting results, interval distribution results, and continuous time interval distribution results.

5. An alarm method for earthquake emergency response according to claim 2, characterized in that, Based on the path information in the valid alarm data combination, cross-validation is performed on the primary alarm data of different paths to confirm that the number of overlaps in node type, propagation level, and source branch dimension of the path source meets the preset overlap threshold condition, generating path independence results, including: Based on the path information in the valid alarm data combination, extract the node sequence and propagation direction information corresponding to each path to generate a path node set. Based on the set of path nodes, the nodes between different paths are compared one by one to determine the common nodes between the paths and generate the node overlap result. Based on the node overlap results, the node positions in the path are classified and processed. The independence of the starting node, relay node and the ending node are analyzed separately to generate node type independence results. The path length result is generated by statistically analyzing the propagation hop count in the path based on the path node set. Based on the path length results, different paths are compared to determine the differences in propagation levels between paths and generate propagation level difference results. The entry directions of the paths are compared based on the path information to determine whether the paths originate from the same source branch, and a source branch determination result is generated. The results are comprehensively verified based on the results of node type independence, propagation level difference, and source branch determination. When the number of overlaps in the three dimensions of node type, propagation level, and source branch is less than the preset overlap threshold, a path independence result that meets the preset independence condition is generated; otherwise, a path independence result that does not meet the preset independence condition is generated.

6. The alarm method for earthquake emergency response according to claim 2, characterized in that, The vibration intensity thresholds in the valid alarm data combinations are weighted and integrated to generate unified vibration intensity parameters, including: Based on the combination of valid alarm data, extract the vibration intensity threshold, path information and time identifier corresponding to each primary alarm data; The propagation hop count of each path is statistically processed based on the path information to generate path length marking results; The node hierarchical positions of each path are parsed based on the path information to generate hierarchical position marking results; The arrival times of each path data are sorted according to the time identifier to generate a time sequence label result; Based on the path length marking results, the path propagation hop count is divided into intervals, and the path length weight is assigned to the corresponding vibration intensity threshold according to the interval where the path propagation hop count is located. The path length weight is negatively correlated with the propagation hop count. Based on the hierarchical location marking results, the node hierarchical location is divided into intervals, and the corresponding vibration intensity threshold is assigned a hierarchical weight according to the interval where the node hierarchical location is located. The hierarchical weight has a preset functional relationship with the node hierarchical depth. Based on the time sequence marking results, the arrival time order of each path data is sorted, and time weights are assigned to the corresponding vibration intensity thresholds according to the sorting sequence number, wherein the time weights decrease with the arrival time order. The results of path length weight, hierarchy weight, and time weight are combined and processed, and the weight values ​​are superimposed to generate a comprehensive weight result. The intensity data set is integrated and processed based on the comprehensive weighting results. Each vibration intensity threshold is weighted and accumulated with its corresponding comprehensive weight, and the accumulated result is normalized to generate a unified vibration intensity parameter.

7. An alarm system for earthquake emergency response, characterized in that, The system, used in the method of any one of claims 1 to 6, comprises: The network construction module is used to build a distributed alarm network consisting of earthquake monitoring nodes, regional relay nodes, and terminal alarm nodes. The primary alarm generation module is used to process the initial seismic wave signal when the earthquake monitoring node detects it, generate primary alarm data containing a vibration intensity threshold, node identifier, and time identifier, and send the primary alarm data to adjacent regional relay nodes. The step of obtaining the vibration intensity threshold includes: continuously acquiring seismic wave signals through sensors in the earthquake monitoring node, converting the raw vibration data into electrical signal data, and performing noise reduction and filtering; extracting features from the filtered signal to obtain vibration amplitude variation information within a preset time period, and determining the vibration intensity level based on the vibration amplitude; mapping the vibration intensity level to the corresponding vibration intensity threshold range according to a preset vibration intensity level classification rule, and selecting the corresponding threshold as the vibration intensity threshold. The step of obtaining the time identifier includes: reading the local time of the earthquake monitoring node and writing it into the data as the time identifier. The statistical processing module is used to: extract the sending node identifier and time identifier from the primary alarm data received by relay nodes in each area, and generate a node source information set; differentiate the sending paths according to the node source information set, and mark them according to the node's hierarchical position in the distributed alarm network and historical forwarding count, generating path structure information and corresponding path identifiers; group primary alarm data with different path sources according to the path structure information, generating path data groups; statistically process the number of path data groups to determine the number of different sending paths, generating path quantity information; sort the time identifiers in each path data group within a preset time window, and generate an arrival time sequence according to the order of the time identifiers; compare the time identifiers of different path data groups pairwise according to the arrival time sequence to determine the time interval relationship between the time identifiers, generating a time interval set; and statistically process the time interval distribution of each path data group according to the time interval set to determine the time interval distribution characteristics between each path data group. The judgment generation module is used to determine the threshold of the time difference between primary alarm data from different paths based on the path quantity information and time interval distribution characteristics, and to impose consistency constraints on the distribution state of the time difference based on the time interval distribution characteristics to generate valid alarm data combinations; and to perform path independence verification on the valid alarm data combinations to generate relay alarm data. The broadcast forwarding module is used by relay nodes in each area to broadcast the relay alarm data, send the relay alarm data to the terminal alarm nodes within its coverage area, and forward it to relay nodes in other areas with path identifiers to generate diffuse alarm data. The terminal triggering module is used to receive and deduplicate alarm data from the terminal alarm node according to the path identifier, and to determine the trigger for non-repeated alarm data based on the vibration intensity threshold. When the triggering conditions are met, an audible and visual alarm signal is generated to obtain a valid alarm triggering result. The suppression module is used to suppress alarm output when the regional relay node does not generate relay alarm data within a preset time window.

8. A computing device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, A computer-readable storage medium stores a program that, when executed by a processor, implements the method as described in any one of claims 1 to 6.

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