Controllable portable monitoring and early warning system for civil aviation passenger plane luggage compartment and method thereof

Abstract

The application provides a controllable portable monitoring and early warning system for a civil aviation passenger plane luggage compartment and a method thereof, and relates to the technical field of luggage compartment monitoring and early warning. The system comprises the following steps: obtaining the communication quality parameters and the current power parameters of each monitoring node in the luggage compartment; constructing a directed graph with each monitoring node as a vertex and the communicable connection between each monitoring node as a directed edge; determining difficult nodes with communication quality parameters lower than a preset threshold; calculating several candidate paths from any difficult node QR to the total end node in the directed graph; assigning a final path to each difficult node according to the candidate paths of each difficult node, and sending the routing information corresponding to the final path to the corresponding monitoring node, so that each monitoring node transmits the collected monitoring data to the total end node according to the corresponding routing information; and the application significantly improves the reliability of data transmission and the network's invulnerability.

Description

Technical Field

[0001] This invention relates to the field of baggage compartment monitoring and early warning technology, and in particular to a controllable portable monitoring and early warning system and method for the baggage compartment of civil aircraft. Background Technology

[0002] With the increasing prevalence of passengers carrying devices containing lithium batteries on airplanes, lithium battery thermal runaway has become a major safety hazard in enclosed baggage compartments. Currently, the fire alarm systems commonly installed on commercial airliners are mainly fixed smoke detectors, usually located in the cargo hold or passenger cabin ventilation ducts. These systems only trigger an alarm after a large amount of smoke is produced by an open flame, and cannot provide early warning of abnormal temperature rises and characteristic gases generated in the early stages of lithium battery thermal runaway. Furthermore, due to the limitations of wired network architecture, the alarm can only indicate a general area and cannot pinpoint the specific baggage compartment. In addition, these systems are integrated and deployed at the aircraft's factory, resulting in complex wiring. Adding or upgrading them to existing fleets requires large-scale modifications, which are massive projects and costly, making rapid widespread adoption difficult. Some existing solutions attempt to use wireless sensor networks for environmental monitoring, but their routing strategies are usually based on fixed topologies or simple relays, failing to consider the real-time impact of dynamic factors such as luggage stacking and metal partitions in aircraft cabins on wireless signals. When the quality of direct communication links between some sensor nodes and the central terminal deteriorates due to signal attenuation or obstruction, existing solutions lack effective adaptive routing adjustment mechanisms, easily leading to data loss or communication interruptions, resulting in monitoring blind spots and failing to meet the high reliability requirements of aviation safety monitoring for data transmission. Furthermore, existing wireless sensing solutions typically rely solely on hop count or single-link signal strength for path planning, neglecting to comprehensively consider the power consumption balancing of relay nodes. This causes some nodes to prematurely exhaust their power due to excessive forwarding tasks, shortening the overall effective lifespan of the monitoring network. Summary of the Invention

[0003] To address the aforementioned technical problems, the technical solution adopted by this invention is as follows:

[0004] According to a first aspect of this application, a portable monitoring and early warning method for the baggage compartment of a controllable civil aircraft is provided, comprising the following steps:

[0005] S100, acquire the communication quality parameters and current power parameters of each monitoring node in the luggage compartment; the communication quality parameters include the communication quality between each monitoring node and other monitoring nodes, and the communication quality between each monitoring node and the central terminal node; the monitoring nodes are used to monitor the environmental data in the corresponding luggage compartment;

[0006] S200: Based on the communication quality parameters and current power parameters of each monitoring node, a directed graph is constructed with each monitoring node as a vertex and the communicable connections between monitoring nodes as directed edges, and a comprehensive weight is assigned to each directed edge; the comprehensive weight is determined based on the communication quality parameters corresponding to the directed edge and the current power parameters of the target monitoring node to which the directed edge points, and the comprehensive weight is negatively correlated with the communication quality parameters and the current power parameters;

[0007] S300, based on the communication quality parameters between each monitoring node and the central terminal node, determine the difficult nodes whose communication quality parameters are lower than a preset threshold;

[0008] S400, for any difficult node QR, calculate several candidate paths from QR to the total end node in the directed graph; the several candidate paths are selected after being sorted by path cost from smallest to largest, and the path cost is the sum of the comprehensive weights of each directed edge contained in the corresponding candidate path.

[0009] S500: Based on the candidate paths of each difficult node, a final path is assigned to each difficult node, and the routing information corresponding to the final path is sent to the corresponding monitoring node, so that each monitoring node transmits the collected monitoring data to the main node according to the corresponding routing information.

[0010] According to another aspect of this application, a controllable portable monitoring and early warning system for the baggage compartment of a civil aircraft is also provided, comprising:

[0011] Several monitoring nodes are deployed in various baggage compartments of a civil aircraft. Each monitoring node includes an environmental data acquisition unit, a wireless communication module, and a power detection module. The environmental data acquisition unit includes a temperature sensor and / or a gas sensor to collect environmental data within the corresponding baggage compartment. The monitoring node periodically sends broadcast detection signals and receives feedback signals to obtain communication quality parameters between itself and other monitoring nodes and the central terminal node. It then reports the communication quality parameters, its current power parameters, and the collected environmental data to the central terminal node.

[0012] A central node is located in the cabin of a civil aircraft and includes a wireless communication module and a data processing module. The data processing module is configured to execute the controllable portable monitoring and early warning method for the baggage compartment of a civil aircraft as described in the first aspect, and to send the generated routing information to the corresponding monitoring node through the wireless communication module.

[0013] The present invention has at least the following beneficial effects:

[0014] This invention provides a portable monitoring and early warning method for the baggage compartment of a controllable civil aircraft. By acquiring the communication quality parameters and current power parameters of each monitoring node, a directed graph is constructed with monitoring nodes as vertices and communicable connections as directed edges. Each directed edge is assigned a comprehensive weight negatively correlated with communication quality and the target node's power level. This ensures that route selection simultaneously considers communication reliability (prioritizing links with superior signal quality) and network energy balance (prioritizing nodes with sufficient power as relays to prevent some nodes from prematurely exhausting due to overload forwarding), extending the effective lifespan of the overall monitoring network. Furthermore, this invention identifies difficult nodes with communication quality below a preset threshold. For each difficult node, several candidate paths are calculated, sorted by path cost from smallest to largest. The path cost is the sum of the comprehensive weights of all included directed edges. Each communication-impaired node can obtain multiple optimal transmission paths to choose from. Finally, based on the candidate paths of each difficult node, a final path is assigned to each difficult node and routing information is sent out. This enables each monitoring node to transmit the collected monitoring data to the central node according to the corresponding routing information. This achieves accurate identification of communication-impaired nodes, dynamic multi-path planning, and adaptive routing allocation under the complex electromagnetic environment of the cabin and dynamic baggage obstruction conditions. It effectively avoids data loss or communication interruption caused by the degradation of some link quality, eliminates monitoring blind spots, and significantly improves the reliability of data transmission and the resilience of the network. Moreover, each monitoring node only needs to report communication quality and power parameters and transmit data according to the sent routing information. It does not need to have complex routing calculation capabilities, which reduces the hardware cost and power consumption of the nodes and is suitable for rapid deployment in the baggage compartment of existing passenger aircraft. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart of a portable monitoring and early warning method for the baggage compartment of a controllable civil aircraft provided in an embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] It should be noted that, based on this disclosure, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects set forth herein can be used to implement the device and / or practice the method. Furthermore, this device and / or practice the method can be implemented using other structures and / or functionalities besides one or more of the aspects set forth herein.

[0019] The following will refer to Figure 1 The flowchart shown is for a portable monitoring and early warning method for the baggage compartment of a controllable civil aircraft, which introduces such a method.

[0020] In this embodiment, the term "master node" refers to a handheld smart terminal (such as a PAD used by flight attendants) installed in the cabin of a civil aircraft. Its internal hardware integrates a ZigBee coordinator module, serving as the data aggregation center and control hub for the entire monitoring network. "Monitoring node" refers to a wireless sensing device deployed in each passenger cabin's baggage compartment. Each baggage compartment has one monitoring node, used to collect environmental data such as temperature and gas concentration within that compartment, and possesses wireless communication capabilities. The monitoring nodes and the master node self-organize to form a wireless mesh network via the ZigBee protocol, and data can be transmitted from the monitoring nodes to the master node through multi-hop relay.

[0021] It should be noted that the specific method by which each monitoring node obtains communication quality parameters is as follows: After the system starts up and the network is established, each monitoring node sends a broadcast probe signal to all other monitoring nodes in the network and the central node at a preset fixed time interval (e.g., once every 10 minutes). Nodes receiving the broadcast probe signal immediately return a feedback signal. The sender calculates the communication quality parameters with the node based on the received feedback signal. These communication quality parameters can be characterized using Received Signal Strength Indication (RSSI) and / or Signal-to-Noise Ratio (SNR). After data collection, each monitoring node reports its current power parameters along with the communication quality parameters to the central node, which then performs subsequent data processing and path planning.

[0022] When performing route planning, the main end node follows the steps S100 to S500.

[0023] S100, acquire the communication quality parameters and current power parameters of each monitoring node in the luggage compartment; the communication quality parameters include the communication quality between each monitoring node and other monitoring nodes, and the communication quality between each monitoring node and the main terminal node; the monitoring nodes are used to monitor the environmental data in the corresponding luggage compartment.

[0024] In this embodiment, the central node receives communication quality parameters and current battery level parameters reported by each monitoring node in the baggage compartment. The communication quality parameters include the communication quality between each monitoring node and every other monitoring node (i.e., the communication quality parameters between any two monitoring nodes), and the communication quality between each monitoring node and the central node (i.e., the communication quality parameters from each monitoring node directly to the central node). If a communication connection cannot be established between two nodes due to signal attenuation, physical obstruction, or other reasons, the corresponding communication quality parameter is recorded as an invalid value or a zero value, which is reflected in the subsequent directed graph as the absence of a directed edge between the two nodes.

[0025] Each monitoring node reports data in a structured data packet format, containing at least the following fields: source node identifier (Source ID), target node identifier (Target ID), communication quality parameter value, current power parameter value, and timestamp. Upon receiving the data packets from each monitoring node, the central node parses, categorizes, and stores all data packets according to their node identifiers, forming a communication quality matrix and power vector for the entire network in the current period, which serve as the data foundation for subsequent steps.

[0026] Furthermore, the communication quality parameters include: signal reception strength indication and / or signal-to-noise ratio; each monitoring node obtains the communication quality parameters by periodically sending broadcast detection signals and receiving feedback signals, wherein the transmission period of the broadcast detection signals is a preset fixed time interval.

[0027] In this embodiment, the communication quality parameters are preferably characterized using Received Signal Strength Indication (RSSI) and / or Signal-to-Noise Ratio (SNR). RSSI measures the power of the radio frequency signal received at the receiver, measured in dBm; a higher RSSI value indicates a stronger received signal and better communication link quality. SNR measures the power ratio between the effective signal received at the receiver and the background noise, measured in dB; a higher SNR value indicates a clearer signal and more reliable communication quality. Both can be used as quantitative indicators of communication quality, and in practical implementation, one or both can be selected based on the hardware capabilities of the monitoring node.

[0028] The period for each monitoring node to send broadcast detection signals is a preset fixed time interval. This period should not be too short to avoid network congestion and excessive power consumption of the nodes due to frequent broadcast signal transmissions; nor should it be too long to avoid failing to track dynamic changes in communication quality caused by factors such as baggage handling and passenger movement within the cabin. In a preferred embodiment, the fixed time interval is set to 10 minutes, meaning that all monitoring nodes in the entire network synchronously perform a broadcast detection process every 10 minutes and report the communication quality parameters obtained from the detection to the central terminal node. In other embodiments, this time interval can also be dynamically adjusted according to the flight phase; for example, it can be set to 10 minutes during the cruise phase and extended to 30 minutes or longer during the ground parking phase to further reduce energy consumption.

[0029] The broadcast detection mechanism described above can acquire bidirectional communication quality information between any two monitoring nodes, thus providing a complete data foundation for the central node to construct a fully connected directed graph. This mechanism is particularly important in cabin baggage compartment monitoring scenarios because there may be complex and uncertain signal obstruction relationships between different compartments within the baggage compartment. Relying solely on the single-point communication quality from each node to the central node is insufficient to determine which nodes have good relay communication conditions, making it impossible to plan optimal relay paths for difficult nodes. Through periodic network-wide broadcast detection, the central node can dynamically grasp the changes in communication quality between any pair of nodes in the entire network, thereby providing accurate data support for subsequent path planning and dynamic self-healing.

[0030] S200: Based on the communication quality parameters and current power parameters of each monitoring node, construct a directed graph with each monitoring node as a vertex and the communicable connections between monitoring nodes as directed edges, and assign a comprehensive weight to each directed edge; the comprehensive weight is determined based on the communication quality parameters corresponding to the directed edge and the current power parameters of the target monitoring node to which the directed edge points, and the comprehensive weight is negatively correlated with the communication quality parameters and the current power parameters.

[0031] This step transforms the raw data obtained in step S100 into a weighted graph model that can be used for path search. The central node constructs a directed graph with all monitoring nodes as vertices and the communicable connections between monitoring nodes as directed edges. Each directed edge in the graph represents data that can be transmitted unidirectionally from one monitoring node to another. After the graph is constructed, the central node assigns a comprehensive weight to each directed edge. The principle for assigning this weight is: the higher the communication quality and the more sufficient the current power of the target node, the smaller the comprehensive weight; that is, the comprehensive weight is negatively correlated with both. This design ensures that the subsequent path search algorithm will naturally tend to select links with good signal quality and sufficient power for relay nodes when choosing a path, thus balancing the reliability of data transmission and the balance of network energy consumption.

[0032] In step S200, assigning a comprehensive weight to each directed edge includes the following steps:

[0033] S210, perform global normalization on the communication quality parameters of each directed edge to obtain normalized communication quality values.

[0034] In this step, the central node performs global normalization on the communication quality parameters of all directed edges obtained in step S100. Global normalization means using the maximum and minimum values ​​of the communication quality parameters of all directed edges in the entire network within the current period as the normalization benchmark, rather than processing them independently for a single node or link. Specifically, the central node first calculates the maximum value of the communication quality parameters of all directed edges within the current period. and minimum value For a directed edge from monitoring node i to monitoring node j, its original communication quality parameter value is denoted as... Normalized communication quality value Calculate using the following formula:

[0035] ;

[0036] The reason for using global normalization is that the radio frequency hardware of different monitoring nodes may have individual differences, and the signal propagation environment at different baggage compartments is also different. If the local extrema of each node are used for normalization, it will lead to the incomparability of communication quality values ​​between different nodes, thus affecting the objective evaluation of different links during subsequent path selection. However, by using the unified maximum and minimum values ​​of the entire network as the normalization benchmark, the communication quality of all directed edges can be mapped to a unified [0,1] numerical space, so that the difference in communication quality between any two edges can be truly reflected by the difference in normalized values, thereby ensuring the fairness of path comparison.

[0037] S220 performs global normalization on the current power parameters of each monitoring node to obtain the normalized power value.

[0038] In this step, the central node performs global normalization on the current power parameters of all monitoring nodes obtained in step S100. Similar to step S210, the normalization here also adopts a global approach: the central node calculates the maximum value of the current power parameters of all monitoring nodes within the current period. and minimum value For any monitoring node j, its current raw power parameter value is denoted as... Normalized energy value Calculate using the following formula:

[0039] ;

[0040] The necessity of global normalization lies in the fact that the absolute battery charge value (such as voltage value or remaining capacity percentage) may exhibit systematic deviations between nodes from different batches and at different usage times. Directly using the absolute charge value in weighting calculations may inappropriately exclude some nodes with relatively low absolute charge values ​​but normal overall condition from relay candidate selection. Global normalization maps the charge charge to "the relative position of the node in the overall network charge distribution," more accurately reflecting the charge sufficiency of each node. This allows for priority selection of nodes with the most abundant charge as relays during path selection, achieving a more balanced energy consumption across the entire network.

[0041] S230, based on monitoring nodes To monitoring nodes Normalized communication quality value and the target monitoring node pointed to by the directed edge Normalized energy value Determine from the monitoring node To monitoring nodes The combined weight of directed edges ;

[0042] ;

[0043] in, and These are preset weighting coefficients used to balance the importance of communication quality and power consumption in path selection, and satisfy... .

[0044] In this step, the master node uses the normalized communication quality value obtained in step S210. and the normalized charge value obtained in step S220 Calculate the combined weight of the directed edges from monitoring node i to monitoring node j. The calculation formula is:

[0045] ;

[0046] in, and These are preset weighting coefficients used to adjust the relative importance of communication quality and power consumption in path selection, and satisfy the following conditions: .

[0047] As can be seen from the formula, the overall weight The range of the value is [0,1], and the smaller the value, the better the directed edge. Since and All values ​​have been normalized to the [0,1] interval. The better the communication quality or the more power the target node has, the closer the corresponding normalized value is to 1. The closer the value is to 0, the more likely the link will be selected during path searching; conversely, the lower the communication quality or the lower the target node's battery level, the more likely it is to be selected. The closer the value is to 1, the lower the priority of the selected link.

[0048] For directed edges directly reaching the central node, the normalized energy value of the central node is used when calculating the overall weight. Setting it to 1 means the main node's battery is considered to be at its maximum capacity; therefore, the overall weight of directly accessible edges is determined solely by communication quality. The rationale for this approach is that the main node is located inside the cabin and can be charged by flight attendants at any time. Its range is not limited by battery power and does not need to be considered in energy balance.

[0049] Weighting coefficient and The value can be flexibly configured according to the actual application scenario. For example, if the monitoring system has higher requirements for data reliability, then... Set it to a larger value (e.g., 0.7). Setting it to 0.3 allows communication quality to dominate path selection; if the system has higher requirements for node endurance balancing, then... Set to a larger value. In the aviation safety monitoring scenario of this invention, data transmission reliability takes precedence over energy saving, and therefore a larger value is preferred. , .

[0050] Furthermore, the weighting coefficients α and β can be dynamically determined as follows:

[0051] The main terminal node obtains the average power parameter B of all monitoring nodes in the current period. avg .

[0052] According to the average power parameter B avg The values ​​of the weighting coefficients α and β are dynamically adjusted based on the preset threshold range in which the range is located.

[0053] When B avg When the threshold is greater than or equal to the first preset threshold, α takes the first value, β takes the second value, and α > β;

[0054] When B avg When the first preset threshold is less than or equal to the second preset threshold, α takes the third value, β takes the fourth value, and α < β; wherein, the first preset threshold is greater than the second preset threshold, the first value is greater than the third value, and the second value is less than the fourth value.

[0055] When all nodes in the network have sufficient power, the system can prioritize ensuring communication quality (α is relatively large); when the power of all nodes is relatively low, the system should prioritize energy saving and prioritize nodes with high power as relays (β is relatively large). By introducing a dynamic adjustment mechanism for weight coefficients based on the average power of the entire network, the routing strategy can adaptively change its preference for "communication quality" and "node power" according to the overall energy state of the network, overcoming the shortcomings of fixed-weight schemes that cannot adapt to dynamic changes in network status. When nodes have sufficient power, priority is given to ensuring the reliability of data transmission; when power is scarce, a proactive energy-saving strategy is adopted to extend the overall network lifespan. This mechanism achieves autonomous and coordinated optimization of system energy consumption and communication performance, effectively improving the monitoring network's continuous working capability and environmental adaptability in long-endurance, multi-segment missions.

[0056] In this embodiment, the comprehensive weight calculation method constructed in steps S210 to S230 achieves a two-dimensional weighted fusion and global normalization decision of communication quality and node power consumption. Compared with the existing wireless sensor network routing schemes that rely solely on hop count or single-link signal strength, this method can more comprehensively and accurately evaluate the overall merits of each candidate link, ensuring that the path search result is optimal not only in communication quality but also in energy consumption balance. Simultaneously, by introducing global normalization, the interference of dimensions caused by hardware and environmental differences between different nodes is eliminated, providing a unified mathematical benchmark and fairness for cross-node and cross-link weight comparisons. Furthermore, the flexible adjustment mechanism of weight coefficients α and β allows this method to adapt to different flight schedules, seasons, and aircraft models with varying priorities regarding monitoring reliability and battery life, exhibiting good scenario adaptability and portability. The design that a smaller comprehensive weight value indicates a better link allows the subsequent path search algorithm to directly minimize the path cost using the sum of weights without additional conversion, reducing computational complexity and improving the real-time performance of path planning.

[0057] S300: Based on the communication quality parameters between each monitoring node and the central terminal node, identify the difficult nodes whose communication quality parameters are lower than a preset threshold.

[0058] The main node obtains the communication quality parameters between each monitoring node and the main node in step S100. Monitoring nodes with communication quality parameters below a preset threshold are selected and identified as difficult nodes. The preset threshold can be set according to the actual needs of aviation safety monitoring; for example, it can be set to -75dBm (corresponding to the RSSI value). When the RSSI value between a monitoring node and the central node is below -75dBm, it is determined that the direct communication quality between that node and the central node does not meet reliability requirements, and a relay path needs to be planned for it.

[0059] For monitoring nodes whose communication quality parameters reach or exceed the preset threshold, the direct communication link between them and the central node is of good quality, requiring no additional path planning. These nodes directly transmit the collected monitoring data to the central node via a single hop. However, for difficult nodes whose communication quality parameters are below the preset threshold, it indicates that the reliability of their direct data upload is insufficient. Data relay forwarding through one or more intermediate monitoring nodes is required. Therefore, subsequent steps S400 and S500 need to be executed to plan the optimal transmission path for each difficult node.

[0060] This step narrows down the scope of path planning by using threshold filtering, and only targets nodes with communication obstructions, thereby reducing the overall computational overhead of the system.

[0061] S400, for any difficult node QR, calculate several candidate paths from QR to the total end node in the directed graph; the several candidate paths are selected after being sorted by path cost from smallest to largest, and the path cost is the sum of the comprehensive weights of each directed edge contained in the corresponding candidate path.

[0062] This step generates multiple optimal transmission paths for each difficult node. For any difficult node, the end node searches the constructed weighted directed graph for all reachable paths from that node to the end node, calculates the path cost of each path (i.e., the sum of the weights of all directed edges contained in the path), and sorts them according to their path costs from smallest to largest. The top-ranked paths are selected as candidate paths for that difficult node. This step reserves multiple paths for each difficult node, rather than providing only one optimal path, to allow for selection space in subsequent path merging steps, which helps reduce the number of nodes performing relay forwarding functions in the network.

[0063] Furthermore, step S400 includes the following steps:

[0064] S410, using the combined weight of each directed edge in the directed graph as the path search cost, the Dijkstra algorithm is used to calculate the shortest path L from the difficult node QR to the total terminal node with the minimum path cost. min and L min As the first candidate path.

[0065] In this step, the total end node is determined by the combined weight of each directed edge in the directed graph constructed in step S200. As the cost of path search, Dijkstra's algorithm is used to calculate the shortest path with the minimum cost from the difficult node QR to the final endpoint T, denoted as . and will As the first candidate path.

[0066] Dijkstra's algorithm is a classic single-source shortest path algorithm suitable for directed graphs with non-negative edge weights. The core idea is to start from the initial node and progressively determine the shortest paths from the initial node to all other nodes in the graph in ascending order of path cost, until the goal node is reached. The specific execution flow of the algorithm is as follows:

[0067] (1) Initialization. Mark the difficult node QR as visited and set... (The distance from the starting node to itself is zero), set (The distance from the starting node to all other nodes is initially infinite). Create a priority queue to store candidate nodes to be processed, and sort the queue in ascending order according to the current dist value of the nodes.

[0068] (2) Node expansion. Take the node u with the smallest dist value from the priority queue (the first node taken is QR), and traverse all directed edges originating from u in the directed graph. Perform a relaxation operation on each neighbor node v pointed to by each edge: if Then update And add v to the priority queue.

[0069] (3) Repeat step (2) until the priority queue is empty or the end node T is marked as visited.

[0070] (4) Path backtracking. The algorithm terminates when the endpoint T is marked as visited. Starting from the endpoint T, backtracking backward along the predecessor nodes to the difficult node QR yields the shortest path with the minimum path cost. and its path cost .

[0071] S420, based on the (k-1)th shortest path already found, the K shortest path algorithm is used to perform deviation search on the path, and the path with the minimum cost from the difficult node QR to the total terminal node is obtained as the candidate path; where k is a preset positive integer, and k≥2.

[0072] In this step, in the already found number Shortest path ( Based on this, the K-Shortest Paths (KSP) algorithm is used to perform deviation search on the path, obtaining the first K paths with the minimum cost from the difficult node QR to the final endpoint T as a candidate path set. Here, K is a preset positive integer, and... In a preferred embodiment, K is set to 3, meaning that each difficult node receives 3 candidate paths.

[0073] The core idea of ​​the K shortest path algorithm is to use known prior information to find the shortest path to the nearest shortest path. Based on the previous shortest paths, the k-th shortest path is searched using a "deviation" strategy. Specifically, for the previous shortest path... At each node it passes through, it attempts to "deviate"—that is, at that node it chooses a different path. Take a new edge from the edge used at the current node, and then use Dijkstra's algorithm to calculate the shortest path to the final node starting from the end node of this new edge. Concatenate the path segment before the node with the newly calculated suffix path segment to form a new candidate path. Select the path with the minimum path cost that has not yet been added to the result set from all the newly generated candidate paths as the k-th shortest path.

[0074] Taking the candidate path search from the difficult node QR to the final node T as an example, the detailed execution flow of the KSP algorithm is as follows:

[0075] (1) The shortest path obtained in step S410 (Right now Add to the result path set and will This serves as the current baseline path.

[0076] (2) For to Repeat the following sub-steps:

[0077] (2a) Take the current reference path Each node along the path, excluding the final endpoint T, is selected as a candidate deviation node. Let... The sequence of nodes traversed is Then the deviation from the node is .

[0078] (2b) For each deviation node ( ), send QR to The path segment is fixed as The corresponding prefix (i.e.) ), and then from Start by finding an "offset edge"—an edge whose terminal node is different from the one on the other side. middle The next-hop node used, and the complete path formed after adding this edge is not connected to the previous one. It is identical to any existing path in the path.

[0079] (2c) Starting from the end node of the offset edge, use Dijkstra's algorithm to calculate the shortest path to the total end node T as the suffix path segment.

[0080] (2d) Concatenate the fixed prefix path segment, deviation edge, and suffix path segment to form a complete candidate path, calculate the path cost of the candidate path (prefix path cost + deviation edge combined weight + suffix path cost), and add the candidate path to the candidate set. middle.

[0081] (3) From the candidate set Select the candidate path with the minimum path cost and remove it. And add to the result path set In the context of the k-th shortest path, .

[0082] (4) Repeat steps (2) to (3) until the result path set is obtained. It contains K paths, or a candidate set. Empty (at this time, the actual number of reachable paths is less than K, and the actual number shall prevail).

[0083] For example: Suppose a difficult node In the directed graph topology leading to the terminal node T, the values ​​on each directed edge represent the overall weight (calculated according to the normalization formula in step S230; each weight value is in the range [0,1], with smaller values ​​indicating better links). For ease of explanation, assume the graph contains nodes A, B, C, D, and the terminal node T, and the overall weights of each edge are as follows: , , , , , , , , , , .

[0084] First, Dijkstra's algorithm is used from... Perform a shortest path search on T to obtain the first shortest path. : The path cost is .

[0085] Subsequently, a KSP deviation search is performed (assuming K=3). The baseline path is (Q). e (A,C,T), the offset node is A, C.

[0086] Off-node Deviation: Fixed prefix is ​​empty, select different middle New Frontier Using a weight of 0.35 as the offset edge, the shortest path from B to T is calculated using Dijkstra's algorithm. The shortest path from B to T is... The cost is Generate candidate paths The total cost is .

[0087] Deviation at node A: fixed prefix (Cost 0.15), choose a different option middle New Frontier (Weight 0.75) is used as an offset edge, with a suffix cost of 0 starting from T, generating candidate paths. The total cost is .

[0088] Deviation at node C: fixed prefix (cost ), choose different middle The new edge – in this example, C has no other outgoing edges, and there are no valid candidate paths for this offset position.

[0089] Select the candidate path with the minimum path cost from the candidate set: (Cost is 0.70), as the second shortest path .

[0090] by Perform the next round of deviation search based on the baseline path. The nodes passed through are (Q) e (,B,C,T), the offset node is B, C.

[0091] Off-node Deviation: Choosing something different New Frontier (Weight 0.15) Calculate the shortest path from A to T using Dijkstra's algorithm. The shortest path from A to T is... The cost is Generate candidate paths The path already exists in the result path set (i.e.) ),give up.

[0092] Deviation at node B: fixed prefix (Cost 0.35), choose a different option New Frontier (Weight 0.65) is used as an offset edge, with a suffix cost of 0 starting from T, generating candidate paths. The total cost is .

[0093] Deviation at node C: fixed prefix (cost ), choose different The new edge – In this example, C has no other outgoing edges, and there are no valid candidate paths.

[0094] Select the candidate path with the minimum path cost from the candidate set: (Cost is 1.00), as the third shortest path .

[0095] The final K candidate paths are: The cost is 0.60; The cost is 0.70; The cost is 1.00.

[0096] The path costs mentioned above are all cumulative values ​​of normalized comprehensive weights; the smaller the value, the better the overall performance of the path. It can be seen that although the three candidate paths have similar costs (0.60, 0.70, 1.00), the combinations of intermediate nodes they pass through are different. Using {A,C} Using {B,C}, Using {B}), this provides ample room for choice in the path merging process in the subsequent step S500. The end node can flexibly select the candidate path with the most overlapping nodes based on the path distribution of other difficult nodes, so as to minimize the number of routing nodes in the entire network.

[0097] In this embodiment, step S410 uses Dijkstra's algorithm to calculate the absolute shortest path from the difficult node to the terminal node as the first candidate path. This ensures that a theoretically optimal transmission path can always be found in any dynamically changing cabin environment, providing the most basic reliability guarantee for data reporting from the difficult node. Step S420 uses the K-shortest path algorithm to perform a systematic deviation search based on the found shortest path. This efficiently obtains multiple candidate paths with the second and third smallest path costs without significantly increasing computational complexity, providing sufficient choice for subsequent steps in path allocation and routing node merging. In addition, it can flexibly select and merge candidate paths that overlap with existing paths based on the path distribution of other difficult nodes, thereby minimizing the number of routing nodes in the entire network and balancing network energy consumption. The combined use of Dijkstra's algorithm and KSP algorithm not only ensures the accurate solution of the absolute optimal path, but also achieves efficient enumeration of suboptimal paths in the "neighborhood" of the optimal path through the deviation search mechanism. Compared with the method of enumerating all reachable paths and then sorting them uniformly, the computational complexity is greatly reduced, significantly reducing the computation time and power consumption of the total end nodes, and improving the response speed of the system in real-time path planning during flight.

[0098] S500: Based on the candidate paths of each difficult node, a final path is assigned to each difficult node, and the routing information corresponding to the final path is sent to the corresponding monitoring node, so that each monitoring node transmits the collected monitoring data to the main node according to the corresponding routing information.

[0099] This step is the final execution stage of path planning. The master node assigns a final path to each difficult node based on the candidate paths for each difficult node. During allocation, the communication urgency of each difficult node is considered, and multiple transmission paths for difficult nodes are merged at intermediate nodes as much as possible to minimize the number of new routing nodes in the network. After the final path allocation is completed, the master node converts the final path corresponding to each difficult node into routing information and sends it to the corresponding monitoring nodes. Upon receiving the routing information, each monitoring node transmits the collected monitoring data, such as temperature and gas concentration, to the master node via multi-hop relay according to the specified path, completing data aggregation.

[0100] Furthermore, in step S500, assigning a final path to each difficult node includes the following steps:

[0101] S510 sorts the difficult nodes from low to high according to the communication quality parameters between each difficult node and the main node, generating a priority sequence of difficult nodes, with the difficult node with the lowest communication quality parameter having the highest priority.

[0102] In this step, the master node uses the original values ​​of the communication quality parameters between all the difficult nodes and the master node as determined in step S300. All difficult nodes are sorted in ascending order to generate a priority sequence. The difficult node with the lowest communication quality parameter has the highest priority and is processed first in the subsequent path allocation process.

[0103] The reason for adopting this prioritization rule is that the more difficult a node is in terms of communication quality, the less reliable its direct link with the central node is. It requires relay forwarding to ensure data transmission, and therefore should be prioritized for allocation of the optimal transmission path to ensure that the node can obtain a usable communication link in the most urgent situation. If the priority order were reversed (i.e., difficult nodes with better communication quality were processed first), it might result in the worst-performing difficult node being unable to obtain the optimal transmission path when some high-quality relay resources are already occupied, thus affecting the overall data reliability of the network.

[0104] In addition, for difficult nodes with the same communication quality parameters, a second priority rule can be used for sorting. For example, nodes can be sorted from low to high according to their current power parameters, and nodes with lower power levels need to obtain reliable relay paths first.

[0105] S520 assigns the candidate path with the lowest path cost among the corresponding candidate paths to the highest priority difficult node as the final path of the difficult node, and marks the intermediate nodes traversed by the final path, excluding the difficult node itself and the end node, as occupied routing nodes.

[0106] In this step, the main node selects the highest priority difficult node (i.e., the node with the worst communication quality with the main node) from the priority sequence, and chooses the candidate path with the lowest path cost from the candidate path set obtained in step S400 as the final path for that difficult node. Selecting the path with the lowest path cost means that this path is optimal in terms of both communication quality and relay node power consumption, and can provide the highest quality transmission guarantee for the difficult node with the worst communication conditions.

[0107] Subsequently, the master node marks all intermediate nodes traversed by the final path (i.e., all nodes except the difficult node itself and the master node) as occupied routing nodes. Occupied routing nodes indicate that these nodes have been assigned data forwarding tasks. When processing other difficult nodes later, if the candidate path passes through these nodes, path merging can be achieved (i.e., multiple difficult nodes share the same relay node).

[0108] S530 processes the remaining difficult nodes in descending order of priority. For the current difficult node... :

[0109] Traversal For each candidate path, calculate the set of common intermediate nodes between each candidate path and all assigned final paths, and count the number of common intermediate nodes;

[0110] If there is a candidate path with a greater than zero number of common intermediate nodes, then the candidate path with the largest number of common intermediate nodes is selected. The final path, making Data transmission is merged into the existing path at the common intermediate node;

[0111] If the number of common intermediate nodes for all candidate paths is zero, then select... The candidate path with the minimum path cost among the candidate paths is selected as the candidate path. The final path.

[0112] In this step, the main endpoint processes the remaining difficult nodes that have not yet been assigned a final path, in descending order of priority sequence generated in step S510. For the currently pending difficult node... The specific processing procedure is as follows:

[0113] (1) Traversal For each candidate path, for each candidate path, the set of intermediate nodes it passes through (excluding...) The system compares itself and the set of intermediate nodes of all allocated final paths (excluding the final endpoint) with the set of intermediate nodes of the final paths, calculates the intersection of the two (i.e., common intermediate nodes), and counts the number of common intermediate nodes.

[0114] (2) If there is a candidate path with a number of common intermediate nodes greater than zero, then the candidate path with the largest number of common intermediate nodes is selected as the candidate path. The final path. At this point, The data transmission will be merged into the existing path at the common intermediate node, that is, it starts from this common intermediate node. The data shares subsequent transmission links with existing paths. This path merging method avoids establishing a complete relay link for each difficult node, thereby reducing the number of new routing nodes in the network.

[0115] (3) If If there are no common intermediate nodes between all candidate paths and the assigned paths (i.e., the number of common intermediate nodes is zero), then the candidate path with the lowest path cost among the candidate paths of the difficult node is selected as its final path, and the intermediate nodes traversed by the final path are marked as new routing nodes.

[0116] In this step, by selecting the candidate path with the most common intermediate nodes, the path merging degree can be maximized. That is, the communication problems of as many difficult nodes as possible are solved with as few additional routing nodes as possible. Thus, while ensuring that each difficult node obtains a reliable transmission path, the total number of routing nodes in the entire network is minimized, and the overall energy consumption is reduced.

[0117] For example: Suppose there are three difficult nodes A, B, and C in a cabin baggage compartment monitoring network, and a master node T. In step S300, the direct communication quality parameters (RSSI values) between each difficult node and the master node are determined as follows: A is -78dBm, B is -72dBm, and C is -65dBm. The preset threshold is -70dBm, meaning all three nodes are difficult nodes. According to step S510, the communication quality is sorted from low to high, and the priority from high to low is: A (-78dBm), B (-72dBm), and C (-65dBm).

[0118] In step S400, the candidate paths (assuming K=3) for each difficult node are calculated as follows:

[0119] Candidate paths for difficult node A:

[0120] A1: A→X→T, path cost 0.45 (intermediate node: X);

[0121] A2: A→Y→Z→T, path cost 0.50 (intermediate nodes: Y, Z);

[0122] A3: A→U→T, path cost 0.55 (intermediate node: U).

[0123] Candidate paths for difficult node B:

[0124] B1: B→X→T, path cost 0.50 (intermediate node: X);

[0125] B2: B→M→T, path cost 0.55 (intermediate node: M);

[0126] B3: B→Y→Z→T, path cost 0.60 (intermediate nodes: Y, Z).

[0127] Candidate paths for difficult node C:

[0128] C1: C→X→T, path cost 0.55 (intermediate node: X);

[0129] C2: C→N→T, path cost 0.60 (intermediate node: N);

[0130] C3: C→M→T, path cost 0.65 (intermediate node: M).

[0131] According to step S520, the highest priority difficult node A (with the worst communication quality) is processed first: A1 (A→X→T, cost 0.45) with the lowest path cost is selected from its candidate paths as the final path, and the intermediate node X is marked as an occupied route node.

[0132] Proceed to step S530 to process the next difficult node B:

[0133] The common intermediate node of B1 (B→X→T) and the existing path A1 is {X}, and the number of common nodes is 1.

[0134] B2 (B→M→T) has no common intermediate nodes with the existing path A1, and the number of intermediate nodes is 0.

[0135] B3 (B→Y→Z→T) has no common intermediate nodes with the existing path A1, and the number of intermediate nodes is 0.

[0136] There exists a candidate path B1 with a greater than zero number of common intermediate nodes, and it has the largest number of common nodes (1). B1 is selected as the final path for B. B's data is merged into A's path at node X, and A and B share the X→T transmission segment.

[0137] Continue processing the last difficult node C:

[0138] The common intermediate node of C1 (C→X→T) and the existing paths A1 and B1 is {X}, and the number of common nodes is 1.

[0139] C2 (C→N→T) has no common intermediate nodes with the existing path, and the number of intermediate nodes is 0.

[0140] C3 (C→M→T) has no common intermediate nodes with the existing path, and the number of such intermediate nodes is 0.

[0141] C1 is selected as the final path of C, and the data of C is merged into the existing path at the X node.

[0142] The final allocation result is that the three difficult nodes A, B, and C all relay data to the main node T through intermediate node X. Only one additional routing node X is added to the entire network, thus resolving the communication problem of the three difficult nodes. In contrast, if each difficult node independently chooses its own shortest path without path merging, then A choosing A1 and using X, B choosing B1 and also using X, and C choosing C1 and also using X (this example happens to overlap). However, in other topologies such as B choosing B2 or C choosing C2, multiple routing nodes may be required. For example, if B chooses B2 (node ​​M), the entire network needs two routing nodes, X and M, increasing energy consumption. The path merging strategy of this invention minimizes the number of routing nodes by prioritizing the path with the most common intermediate nodes and maximizing path sharing within the limits of topology.

[0143] In this embodiment, the priority-driven path allocation and merging strategy implemented in steps S510 to S530 ensures that the most difficult nodes with the worst communication quality and the most urgent need for relay services can obtain the transmission path with the best overall performance, effectively guaranteeing the data transmission reliability of the nodes with the worst communication conditions in the network. Furthermore, by systematically traversing the candidate paths of each difficult node and prioritizing the merging of paths with the most common intermediate nodes with existing paths, the data transmission of multiple difficult nodes can be efficiently converged at the common relay node, thereby minimizing the number of new routing nodes added to the entire network and reducing the overall network power consumption. The method effectively slows down network segmentation and monitoring blind spots caused by premature battery depletion at some nodes. Furthermore, after path merging, data traffic converges at common nodes, reducing redundant data transmission copies and repeated relays in the network. This lowers the probability of channel contention and data collisions, improving the channel utilization efficiency and overall throughput of the wireless network. Compared to simply selecting the shortest path for each difficult node independently, the path merging method in this embodiment minimizes the number of routing nodes across the network, balances network energy consumption, and significantly improves the efficiency of wireless channel resource utilization, while ensuring that each node obtains a reliable transmission path.

[0144] Furthermore, the method also includes a dynamic replanning step: after each preset replanning cycle, the main node re-executes steps S100 to S500, recalculates the comprehensive weight of each directed edge based on the latest communication quality parameters and current power parameters reported by each monitoring node in the current replanning cycle, and re-identifies the difficult nodes and reassigns the final path to each difficult node.

[0145] In the scenario of monitoring baggage compartments on passenger aircraft, the wireless communication environment is not static but constantly changing. On the one hand, passengers may rummage through their luggage during flight, causing changes in the stacking pattern and obstruction relationships, thereby altering the signal propagation paths and communication quality between monitoring nodes. On the other hand, the battery power of each monitoring node is continuously consumed as it operates, and the rate of power consumption varies among different nodes due to differences in their data reporting frequency and relay forwarding workload. Furthermore, the electromagnetic environment and air pressure conditions within the cabin change during different flight phases, such as takeoff, cruise, and descent. All of these factors may cause the optimal path planned in the previous cycle to no longer be optimal in the current cycle, and some paths may even become unavailable due to relay node battery depletion.

[0146] To address this, this embodiment introduces a dynamic replanning mechanism: after each preset replanning cycle (e.g., every 10 minutes), the central node automatically re-executes steps S100 to S500, namely, re-acquiring the latest communication quality parameters and current power parameters reported by each monitoring node in the current cycle, reconstructing the directed graph and recalculating the comprehensive weight of each directed edge, re-identifying difficult nodes with communication quality below the threshold, recalculating candidate paths for each difficult node, and assigning a final path. The updated routing information is then redistributed from the central node to each monitoring node, and each node immediately transmits data according to the new path.

[0147] Through the aforementioned periodic replanning, the monitoring network acquires the ability to dynamically sense and adaptively adjust, enabling it to track changes in the cabin communication environment and node power status in real time. It always maintains the network topology in an optimal or near-optimal state for the current environment, thereby achieving the technical effect of dynamic network self-healing and avoiding data transmission interruptions and monitoring blind spots caused by environmental changes or node power consumption.

[0148] Furthermore, in step S400, if there is a directed edge in QR that directly reaches the total end node, and the combined weight of the directed edge is less than the path cost of all multi-hop candidate paths of QR, then the direct path that directly reaches the total end node is retained among the several candidate paths corresponding to QR.

[0149] In step S300, a monitoring node is identified as a difficult node because the communication quality parameter between the node and the central node is lower than a preset threshold. This determination indicates that the direct communication quality between the node and the central node does not meet reliability requirements, therefore a relay path needs to be planned for it.

[0150] However, in some situations, even if a node's direct communication quality is below a threshold, the overall weight of its direct links (determined by both communication quality and total battery power) may still be better than the path cost of all multi-hop paths. For example, if a node's direct communication quality is slightly below the threshold, while other nodes that can be used as relays either have worse communication quality or lower battery power, the overall weight of multi-hop paths via relays may actually be greater than that of direct links after being accumulated.

[0151] In the above scenario, if a directed edge exists between the difficult node QR and the end node, and the combined weight of this directed edge is less than the path cost of all multi-hop candidate paths for that difficult node, then this direct path is retained in the candidate path set of QR. In other words, although the communication quality of the direct link does not meet the threshold standard in an absolute sense, it is still the least costly choice in the current network relative comparison.

[0152] The rationale behind this approach lies in the following: the preset threshold is a fixed indicator used to initially screen nodes where communication may be obstructed; while path cost is a relative comparison indicator used to select the optimal transmission path under specific network conditions. When the combined cost of all multi-hop paths is higher than that of the direct path, it means that within the current cycle, forwarding through any intermediate node cannot provide a better overall effect than direct transmission (worse signal or insufficient relay power). In this case, retaining the direct path as one of the candidates avoids unnecessary delays and increased energy consumption caused by "relaying for the sake of relaying," making path selection more rational and efficient. In the subsequent step S500, if the direct path is selected, the difficult node will directly upload data. Although the communication quality is slightly lower than the threshold, it is still within an acceptable range, and the combined cost is minimal, making it the optimal feasible solution under the current conditions.

[0153] Furthermore, during the operation of the baggage compartment monitoring network, due to reasons such as baggage stacking obstruction, metal partition reflection, node battery depletion, or hardware failure, a certain monitoring node may be unable to establish a communication connection with all other nodes in the network (including the main node and other monitoring nodes), thus becoming an "isolated node" in the network. Once an isolated node occurs, the monitoring data for that baggage compartment cannot be uploaded at all, creating a monitoring blind spot. Based on this, the following method is provided:

[0154] S610, the main terminal node monitors the data reporting status of each monitoring node. If no data report is received from any monitoring node in the current period, the monitoring node is marked as a suspected isolated node.

[0155] The central node monitors the data reporting status of each monitoring node in each cycle. Under normal circumstances, each monitoring node reports the environmental data, communication quality parameters, and power parameters it has collected to the central node according to a preset cycle. If the central node does not receive any data report from a monitoring node in the current cycle, it marks that monitoring node as a "suspected isolated node".

[0156] The reason for using "suspected" instead of directly classifying a node as "isolated" is that a monitoring node's failure to report data can be caused by various reasons. For example, the communication link between the node and the central node may be temporarily interrupted due to signal obstruction, but communication between the node and other adjacent monitoring nodes may still be normal. In this case, although the node cannot directly transmit data to the central node, it can complete the reporting through relay by other monitoring nodes, and the node is not truly isolated. Alternatively, the node may fail to deliver data for the current period due to brief electromagnetic interference or packet collisions, but the communication link itself is not interrupted. Therefore, before active verification, it is not advisable to directly classify a node as isolated; marking it as "suspected" first can avoid misjudgments caused by temporary communication failures.

[0157] S620, the master node sends a probe command to all neighboring monitoring nodes of the suspected isolated node, instructing each neighboring monitoring node to send a directional probe signal to the suspected isolated node at maximum transmission power. The probe signal contains the node identifier of the suspected isolated node and a request for response.

[0158] After marking a suspected isolated node, the master node immediately initiates an active verification process, sending probe commands to all neighboring monitoring nodes of the suspected isolated node. "Neighboring monitoring nodes" refer to other monitoring nodes that have successfully established a communication connection with the suspected isolated node (i.e., a directed edge exists) within the most recent normal communication cycle, or monitoring nodes that are physically adjacent to the baggage compartment where the suspected isolated node is located.

[0159] The probe command instructs each adjacent monitoring node to send a directional probe signal to the suspected isolated node at maximum transmission power. The purpose of using maximum transmission power is to maximize the coverage and penetration of the probe signal, especially in extreme cases where the suspected isolated node may be experiencing weak communication signals. This increases the probability of successfully receiving a response signal and avoids misclassifying nodes with poor communication quality as isolated nodes due to insufficient transmission power. The probe signal must contain at least the node identifier of the suspected isolated node and a request for a response, ensuring that only the designated target node responds to the probe signal and preventing interference from other unrelated nodes.

[0160] S630, if an adjacent monitoring node successfully receives the response signal returned by the suspected isolated node within the preset detection timeout threshold, the main node determines that there is currently no isolated node, adds the temporary communication link between the adjacent monitoring node and the suspected isolated node to the directed graph, assigns a comprehensive weight to the temporary communication link, and re-executes steps S400 to S500 to plan a transmission path for the suspected isolated node.

[0161] If, within the preset detection timeout threshold (e.g., 10 seconds), a neighboring monitoring node successfully receives a response signal from a suspected isolated node, it indicates that the node is not truly isolated and still possesses basic communication transmission capabilities. It is merely that the direct communication link with the central node is temporarily interrupted due to temporary obstruction or other reasons.

[0162] At this point, the master node adds the temporary communication link between the adjacent monitoring node and the suspected isolated node to the directed graph and assigns a comprehensive weight to the temporary link according to the comprehensive weight calculation method in step S200. Subsequently, the master node re-executes steps S400 to S500 to plan a transmission path for the suspected isolated node via the adjacent monitoring node and sends the updated routing information to the suspected isolated node. Through this process, the suspected isolated node can resume data communication with the master node through the newly established temporary link, avoiding data loss caused by the interruption of a single link.

[0163] S640, if none of the adjacent monitoring nodes receive any response signal from the suspected isolated node within the preset detection timeout threshold, the main terminal node confirms that the suspected isolated node is an isolated node and generates an isolated node alarm message.

[0164] If none of the adjacent monitoring nodes receive any response signal from the suspected isolated node within the preset detection timeout threshold, it indicates that the suspected isolated node cannot communicate directly with the main node or with any adjacent monitoring node, and is thus confirmed as a true "isolated node".

[0165] At this point, the central node generates an isolated node alarm and displays it on the central interface (such as the display on a flight attendant's handheld tablet). This alarm alerts the crew that the specific baggage compartment corresponding to the isolated node is at risk of communication failure and requires manual inspection of the node's hardware status (e.g., whether the battery is depleted or the equipment is damaged) or whether there are extreme obstructions caused by baggage stacking. Through manual intervention, the crew can promptly implement alternative safety monitoring measures for the baggage compartment, avoiding safety hazards caused by missing monitoring data.

[0166] Furthermore, the method also includes the following steps:

[0167] S700, the central node receives monitoring data reported by each monitoring node according to the routing information. The monitoring data includes at least temperature data and gas concentration data in the corresponding luggage compartment of each monitoring node. The central node performs a graded early warning judgment on the monitoring data of each monitoring node: when the rate of increase of temperature data reported by any monitoring node exceeds the first temperature rise rate threshold, or the rate of increase of gas concentration exceeds the first concentration change rate threshold, a first-level early warning is triggered and displayed on the central node display interface; when the absolute value of temperature data reported by any monitoring node exceeds the temperature safety threshold, or the absolute value of gas concentration data exceeds the concentration safety threshold, a second-level alarm is triggered and the location of the corresponding monitoring node is displayed on the central node display interface.

[0168] (1) Level 1 Warning (Yellow Warning) Judgment. The central terminal node performs the following judgment on the monitoring data of each monitoring node: when the rate of increase of the temperature data reported by any monitoring node exceeds the preset first temperature rise rate threshold, it indicates that there is an abnormal temperature rise trend in the baggage compartment; when the rate of increase of the concentration of volatile organic compounds reported by any monitoring node exceeds the preset first concentration change rate threshold, it indicates that there may be leakage of lithium battery electrolyte or release of characteristic gases generated by thermal decomposition in the baggage compartment. The above two abnormal situations are typical signs of early thermal runaway of lithium batteries. When either condition is met, the central terminal node triggers a Level 1 warning, and displays the baggage compartment icon corresponding to the monitoring node on the central terminal display interface in a prompt manner, and displays the warning type ("abnormal temperature rise" or "abnormal gas concentration"). The Level 1 warning is intended to remind the crew that there is a potential risk in the baggage compartment and that they need to pay more attention.

[0169] (2) Level 2 Alarm (Red Alarm) Judgment. When the absolute value of the temperature data reported by any monitoring node exceeds the preset temperature safety threshold, it indicates that the temperature inside the baggage compartment has risen to a dangerous level; when the absolute value of the smoke concentration data reported by any monitoring node exceeds the preset concentration safety threshold, it indicates that there are smoke particles generated by open flames inside the baggage compartment. When any of the above conditions are met, the central terminal node will trigger a Level 2 alarm, highlight the baggage compartment icon corresponding to the monitoring node on the central terminal display interface, and simultaneously activate the audible and visual alarm device of the central terminal equipment, accurately locate and enlarge the specific location of the alarmed baggage compartment on the cabin layout diagram. A Level 2 alarm indicates an extremely high risk of open flames or impending open flames inside the baggage compartment, requiring the crew to take immediate emergency response measures.

[0170] (3) Location display. Each monitoring node is bound to a specific baggage compartment during system initialization. Therefore, when a secondary alarm is triggered, the central node can accurately locate the corresponding baggage compartment on the pre-stored cabin layout map according to the node identifier of the monitoring node from which the alarm originates, thus achieving compartment-level alarm location.

[0171] Through this step, the reliable data transmission capability ensured by the data acquisition network and path planning mechanism established in the preceding steps is ultimately transformed into a perceptible, locatable, and actionable safety early warning function for the crew. This constitutes a complete monitoring and early warning closed loop from data acquisition and reliable transmission to intelligent analysis and graded early warning, making the entire technical solution fully correspond to the invention theme of "Portable Monitoring and Early Warning Method for Controllable Civil Aircraft Passenger Aircraft Baggage Compartment". Through a two-level threshold design, this invention can issue an early warning in the early stage of lithium battery thermal runaway (abnormal temperature rise or characteristic gas release stage), rather than waiting for an open flame to produce a large amount of smoke before alarming, achieving the technical effect of early warning; at the same time, each alarm message is accurately located to a specific baggage compartment, achieving the technical effect of precise compartment-level positioning.

[0172] Furthermore, although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0173] Embodiments of the present invention also provide a controllable portable monitoring and early warning system for the baggage compartment of a civil aircraft, comprising:

[0174] Several monitoring nodes are deployed in various baggage compartments of a civil aircraft. Each monitoring node includes an environmental data acquisition unit, a wireless communication module, and a power detection module. The environmental data acquisition unit includes a temperature sensor and / or a gas sensor to collect environmental data within the corresponding baggage compartment. The monitoring node is used to periodically send broadcast detection signals and receive feedback signals to obtain communication quality parameters between itself and other monitoring nodes and the central terminal node, and to report the communication quality parameters, its current power parameters, and the collected environmental data to the central terminal node.

[0175] A central node is located in the cabin of a civil aircraft and includes a wireless communication module and a data processing module. The data processing module is configured to execute the controllable civil aircraft baggage compartment portable monitoring and early warning method as described in the above embodiments, and to send the generated routing information to the corresponding monitoring node through the wireless communication module.

[0176] While specific embodiments of the invention have been described in detail by way of examples, those skilled in the art should understand that the examples are for illustrative purposes only and are not intended to limit the scope of the invention. Those skilled in the art should also understand that various modifications can be made to the embodiments without departing from the scope and spirit of the invention.

Claims

1. A portable monitoring and early warning method for the controlled luggage compartment of a civil passenger aircraft, characterized in that, Includes the following steps: S100, acquire the communication quality parameters and current power parameters of each monitoring node in the luggage compartment; the communication quality parameters include the communication quality between each monitoring node and other monitoring nodes, and the communication quality between each monitoring node and the central terminal node; the monitoring nodes are used to monitor the environmental data in the corresponding luggage compartment; S200 constructs a directed graph with each monitoring node as a vertex and the communicable connections between monitoring nodes as directed edges, based on the communication quality parameters and current power parameters of each monitoring node, and assigns a comprehensive weight to each directed edge. The comprehensive weight is determined based on the communication quality parameter corresponding to the directed edge and the current power parameter of the target monitoring node pointed to by the directed edge. The comprehensive weight is negatively correlated with the communication quality parameter and the current power parameter. S300, based on the communication quality parameters between each monitoring node and the central terminal node, determine the difficult nodes whose communication quality parameters are lower than a preset threshold; S400, for any difficult node QR, calculate several candidate paths from QR to the total end node in the directed graph; the several candidate paths are selected after being sorted by path cost from smallest to largest, and the path cost is the sum of the comprehensive weights of each directed edge contained in the corresponding candidate path. S500: Based on the candidate paths of each difficult node, a final path is assigned to each difficult node, and the routing information corresponding to the final path is sent to the corresponding monitoring node, so that each monitoring node transmits the collected monitoring data to the main node according to the corresponding routing information.

2. The portable monitoring and early warning method for the controllable cabin luggage compartment of a civil aviation passenger plane according to claim 1, characterized in that, In step S200, assigning a comprehensive weight to each directed edge includes the following steps: S210, perform global normalization on the communication quality parameters of each directed edge to obtain normalized communication quality values; S220, perform global normalization on the current power parameters of each monitoring node to obtain the normalized power value; S230, based on monitoring nodes To monitoring nodes Normalized communication quality value and the target monitoring node pointed to by the directed edge Normalized energy value Determine from the monitoring node To monitoring nodes The combined weight of directed edges ; ； in, and These are preset weighting coefficients used to balance the importance of communication quality and power consumption in path selection, and satisfy... .

3. The portable monitoring and early warning method for the baggage compartment of a controllable civil aircraft as described in claim 2, characterized in that, and The following relationship must be satisfied: ； in, and These are the maximum and minimum values ​​of the communication quality parameters for all directed edges within the current period, respectively. To monitor nodes To monitoring nodes The original values ​​of the communication quality parameters; ； and These are the maximum and minimum values ​​of the current power parameters for all monitored nodes within the current period, respectively. For monitoring nodes The original value of the current battery level parameter.

4. The portable monitoring and early warning method for controllable civil aircraft baggage compartments according to claim 1, characterized in that, Step S400 includes the following steps: S410, using the comprehensive weight of each directed edge in the directed graph as the path search cost, using Dijkstra algorithm to calculate the shortest path L with the minimum path cost from the difficult node QR to the total end node min , and taking L min as the first candidate path; S420, based on the (k-1)th shortest path already found, the K shortest path algorithm is used to perform deviation search on the path, and the path with the minimum cost from the difficult node QR to the total terminal node is obtained as the candidate path; where k is a preset positive integer, and k≥2.

5. The portable monitoring and early warning method for controllable civil aircraft baggage compartments according to claim 1, characterized in that, In step S500, a final path is assigned to each difficult node, including the following steps: S510: Sort each difficult node and the main terminal node in order of communication quality parameters from low to high, and generate a priority sequence of difficult nodes, with the difficult node with the lowest communication quality parameter having the highest priority. S520: Assign the candidate path with the lowest path cost among the corresponding candidate paths to the hardest node with the highest priority as the final path of the hardest node, and mark the intermediate nodes passed through by the final path, except for the hardest node itself and the end node, as occupied route nodes. S530 processes the remaining difficult nodes in descending order of priority. For the current difficult node... : Traversal For each candidate path, calculate the set of common intermediate nodes between each candidate path and all assigned final paths, and count the number of common intermediate nodes; If there is a candidate path with a greater than zero number of common intermediate nodes, then the candidate path with the largest number of common intermediate nodes is selected. The final path, making Data transmission is merged into the existing path at the common intermediate node; If the number of common intermediate nodes for all candidate paths is zero, then select... The candidate path with the minimum path cost among the candidate paths is selected as the candidate path. The final path.

6. The portable monitoring and early warning method for controllable civil aircraft baggage compartments according to claim 1, characterized in that, The communication quality parameters include: signal reception strength indication and / or signal-to-noise ratio; each monitoring node obtains the communication quality parameters by periodically sending broadcast detection signals and receiving feedback signals, wherein the sending period of the broadcast detection signals is a preset fixed time interval.

7. The portable monitoring and early warning method for controllable civil aircraft baggage compartments according to claim 1, characterized in that, The method further includes a dynamic replanning step: after each preset replanning cycle, the main node re-executes steps S100 to S500, recalculates the comprehensive weight of each directed edge based on the latest communication quality parameters and current power parameters reported by each monitoring node in the current replanning cycle, and re-identifies the difficult nodes and reassigns the final path to each difficult node.

8. The portable monitoring and early warning method for the baggage compartment of a controllable civil aircraft as described in claim 1, characterized in that, In step S400, if there is a directed edge in QR that directly reaches the total end node, and the combined weight of the directed edge is less than the path cost of all multi-hop candidate paths of QR, then the direct path that directly reaches the total end node is retained among the candidate paths corresponding to QR.

9. The portable monitoring and early warning method for controllable civil aircraft baggage compartments according to claim 1, characterized in that, The method further includes the following steps: S610, the main terminal node monitors the data reporting status of each monitoring node. If no data report is received from any monitoring node in the current period, the monitoring node is marked as a suspected isolated node. S620, the main terminal node sends a detection command to all neighboring monitoring nodes of the suspected isolated node, instructing each neighboring monitoring node to send a directional detection signal to the suspected isolated node at maximum transmission power, the detection signal containing the node identifier of the suspected isolated node and a request for response; S630, if an adjacent monitoring node successfully receives the response signal returned by the suspected isolated node within the preset detection timeout threshold, the main terminal node determines that there is currently no isolated node, adds the temporary communication link between the adjacent monitoring node and the suspected isolated node to the directed graph, assigns a comprehensive weight to the temporary communication link, and re-executes steps S400 to S500 to plan a transmission path for the suspected isolated node. S640, if none of the adjacent monitoring nodes receive any response signal from the suspected isolated node within the preset detection timeout threshold, the main terminal node confirms that the suspected isolated node is an isolated node and generates an isolated node alarm message.

10. A portable monitoring and early warning system for the baggage compartment of a controllable civil aircraft, characterized in that, include: Several monitoring nodes are deployed in various baggage compartments of a civil aircraft. Each monitoring node includes an environmental data acquisition unit, a wireless communication module, and a power detection module. The environmental data acquisition unit includes a temperature sensor and / or a gas sensor to collect environmental data within the corresponding baggage compartment. The monitoring node periodically sends broadcast detection signals and receives feedback signals to obtain communication quality parameters between itself and other monitoring nodes and the central terminal node. It then reports the communication quality parameters, its current power parameters, and the collected environmental data to the central terminal node. A central node is located in the cabin of a civil aircraft and includes a wireless communication module and a data processing module; the data processing module is configured to execute the controllable civil aircraft baggage compartment portable monitoring and early warning method as described in any one of claims 1 to 9, and to send the generated routing information to the corresponding monitoring node through the wireless communication module.

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