A secondary cable laying progress monitoring method and system

Abstract

The application discloses a secondary cable laying progress monitoring method and system, and the method comprises the following steps: constructing a laying directed topology graph; collecting construction sound and vibration time sequence data through an environment sensor, and establishing a directed edge and monitoring point mapping relationship; using cable head end wireless beacon positioning to generate a traversed directed edge sequence; extracting a target time sequence data set, adaptively segmenting into action data segments, identifying construction action types, and forming an actual construction action sequence; comparing the actual action sequence with a preset laying procedure standard action sequence template through dynamic time warping, and if the matching degree exceeds a threshold value, then the corresponding path length is accumulated, and the laying progress is calculated. Through the fusion of multi-source sound and vibration data, adaptive action segmentation and sequence comparison, the application realizes real-time and automatic progress monitoring without relying on manual recording, solves the problems of lagging and easy errors in traditional manual recording, and significantly improves the accuracy and timeliness of power engineering cable laying progress management.

Description

Technical Field

[0001] This invention belongs to the field of power engineering construction progress monitoring technology, and in particular relates to a method and system for monitoring the progress of secondary cable laying. Background Technology

[0002] In power engineering projects such as substations and power plants, the laying of secondary cables is a crucial part of the electrical installation phase. Secondary cables are numerous and have complex routes, typically traversing multiple critical locations such as cable trenches, shafts, and terminal boxes. The laying process is lengthy and involves many personnel. Accurate and timely monitoring of the secondary cable laying progress is key to ensuring overall project progress is controllable and to promptly identifying construction delays and work-related conflicts.

[0003] Currently, monitoring the progress of secondary cable laying mainly relies on manual recording and reporting. After completing a section of cable laying, construction workers manually fill in a construction log, which is then compiled and statistically analyzed by management personnel. This method has the following problems: First, information is severely delayed, and management personnel cannot grasp the actual progress on site in real time; second, data accuracy depends on the recording habits of construction workers, which can easily lead to omissions or errors; third, it cannot automatically detect problems such as cable laying sequence conflicts or incorrect paths.

[0004] Some solutions attempt to use radio frequency identification (RFID) or video surveillance technology for progress monitoring. However, RFID solutions can only acquire discrete events of cables passing through specific locations and cannot confirm whether the path segment between two locations has been completed. Video surveillance solutions are easily affected by obstruction and lighting in complex construction environments, resulting in insufficient recognition reliability.

[0005] Therefore, there is a need for a method that can automatically monitor the progress of secondary cable laying in real time and accurately without relying on manual recording. Summary of the Invention

[0006] This invention provides a method, system, electronic device, and computer-readable storage medium for monitoring the progress of secondary cable laying. By constructing a directed topology map of the laying process and combining wireless beacon positioning and environmental sensor perception, it automatically identifies construction actions and infers the laying progress, solving the problems of lag and error in manual recording.

[0007] In a first aspect, the present invention provides a method for monitoring the progress of secondary cable laying, comprising: Obtain the design path data of all secondary cables in the area to be laid, and construct a directed topology graph. The directed topology graph uses key locations on the cable laying path as nodes and path segments between adjacent key locations as directed edges. During the laying operation, environmental sensors installed at multiple preset monitoring points continuously collect time-series data reflecting the construction dynamics near each preset monitoring point. Each directed edge in the laid directed topology graph is associated with the spatial location of at least two preset monitoring points to establish a mapping relationship between the directed edge and the preset monitoring points. For each cable, the wireless signal emitted by the wireless beacon attached to the cable end at a preset time interval is obtained, the wireless signal is received by the signal receiver set at each of the key locations, and the path segment at each time point of the cable end is determined according to the signal strength indication value of the received signal, and the directed edge sequence that the cable end has been traversed is generated. Based on the mapping relationship, extract the time series data of all preset monitoring points associated with a certain directed edge in the directed edge sequence to obtain the target time series data set; The target time series data set is adaptively divided into multiple action data segments corresponding to a single construction action, and the construction action type corresponding to each action data segment is determined. The construction action types determined in sequence are arranged in chronological order to obtain the actual construction action sequence. The actual construction action sequence is compared with the preset standard action sequence template for laying procedures. If the matching degree exceeds the preset procedure completion threshold, the path length value of a certain directed edge is added to the laid length of the cable. The laid length is then divided by the total designed path length of the cable to obtain the laying progress of the cable.

[0008] Secondly, the present invention provides a secondary cable laying progress monitoring system, comprising: The construction module is configured to obtain the design path data of all secondary cables in the area to be laid, and construct a directed topology graph for laying. The directed topology graph for laying uses key location points on the cable laying path as nodes and path segments between adjacent key location points as directed edges. The acquisition module is configured to continuously collect time-series data reflecting the construction dynamics near each preset monitoring point through environmental sensors set at multiple preset monitoring points during the laying operation. The association module is configured to associate each directed edge in the laid directed topology graph with the spatial positions of at least two preset monitoring points, and establish a mapping relationship between the directed edge and the preset monitoring points. The generation module is configured to acquire, for each cable, the wireless signal emitted by the wireless beacon attached to the cable end at a preset time interval, receive the wireless signal through the signal receiver set at each of the key locations, determine the path segment at each time point of the cable end based on the signal strength indication value of the received signal, and generate the directed edge sequence that the cable end has been traversed. The extraction module is configured to extract time-series data of all preset monitoring points associated with a certain directed edge in the directed edge sequence according to the mapping relationship, so as to obtain a target time-series data set; The segmentation module is configured to adaptively segment the target time series data set into multiple action data segments corresponding to a single construction action, determine the construction action type corresponding to each action data segment, and arrange the determined construction action types in chronological order to obtain the actual construction action sequence. The accumulation module is configured to compare the actual construction action sequence with the preset standard action sequence template for laying procedures. If the matching degree of the comparison exceeds the preset procedure completion threshold, the path length value of a certain directed edge is accumulated into the laid length of the cable, and the laid length is divided by the total designed path length of the cable to obtain the laying progress of the cable.

[0009] Thirdly, an electronic device is provided, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the steps of the secondary cable laying progress monitoring method of any embodiment of the present invention.

[0010] Fourthly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor performs the steps of the secondary cable laying progress monitoring method of any embodiment of the present invention.

[0011] The secondary cable laying progress monitoring method and system of this application have the following beneficial effects: By constructing a directed topology graph, the cable laying path is abstracted into a graph structure of nodes and directed edges. The directed edges are spatially nearest neighbored with preset monitoring points, so that the construction activities of each directed edge can be synchronously perceived by at least two monitoring points from different locations. This realizes the spatial coverage extension of construction monitoring from discrete points to continuous path segments, and solves the problem that traditional radio frequency identification schemes can only obtain point information but cannot confirm the laying status of the complete path segment.

[0012] By simultaneously acquiring time-series data of both sound intensity and vibration intensity, adaptive segmentation is performed using the fused energy of sound and vibration. This makes the segmentation highly sensitive to construction activities that generate both sound and vibration, while suppressing environmental interference that only generates a single mode of noise. This effectively distinguishes construction actions from background noise and improves the accuracy of action segmentation.

[0013] The system extracts multidimensional features of sound and vibration in the time and frequency domains for each action data segment and performs cosine similarity matching with a preset construction action feature library. This enables automatic recognition of various typical construction actions such as cable pulling, binding, bending adjustment, cover opening and closing, and personnel movement. The system has rich feature dimensions and strong discriminative power. The recognition results do not depend on the absolute strength of the signal but only focus on the consistency of feature direction. It has good adaptability to different construction distances and environments.

[0014] By flexibly comparing the actual construction action sequence with the standard action sequence template of the laying process, it can automatically handle the repetition or omission of actions caused by differences in construction rhythm. The matching degree of the action sequence is used as the basis for judging the completion of laying. The judgment logic is transparent and the results are interpretable. The generation of each progress data can be traced back to the specific construction action identification result and process comparison process.

[0015] The entire monitoring process requires no manual recording by construction personnel. The complete chain from data acquisition and action recognition to progress calculation is executed automatically, eliminating the problems of lag and errors in manual recording. It provides project managers with real-time and accurate cable laying progress information, significantly improving the automation level and data reliability of secondary cable laying progress management in power engineering. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating a method for monitoring the progress of secondary cable laying according to an embodiment of the present invention; Figure 2 This is a structural block diagram of a secondary cable laying progress monitoring system provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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, 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.

[0019] Please see Figure 1The diagram shows a flowchart of a secondary cable laying progress monitoring method according to this application.

[0020] like Figure 1 As shown, the method for monitoring the progress of secondary cable laying includes the following steps: Step S101: Obtain the design path data of all secondary cables in the area to be laid, and construct a directed topology graph. The directed topology graph uses key location points on the cable laying path as nodes and path segments between adjacent key location points as directed edges.

[0021] In this step, the laying path information of all secondary cables in the area to be laid is first extracted from the design drawings of the substation or power plant. The design drawings are electrical construction drawings in CAD or PDF format, and the drawings indicate the number of each secondary cable, the starting equipment, the ending equipment, and the facilities such as cable trenches, shafts, and terminal boxes along the route.

[0022] For each secondary cable, key locations on the cable laying path are identified and extracted from the design drawings. These key locations include: corners of cable trenches, intersections and branches of cable trenches, entrances and exits of shafts, terminal blocks of distribution cabinets, inlets and outlets of terminal boxes, and interlayer crossing points of cable racks. Each key location has a unique location number and spatial coordinates, which are represented by three-dimensional coordinates in the construction coordinate system.

[0023] Each key location point is assigned a unique node identifier. The node identifier is in the form of a number, starting from 1 and incrementing sequentially. For example, the first key location point is assigned node identifier 1, the second key location point is assigned node identifier 2, and so on. The node identifiers, location numbers, and spatial coordinates of all key location points are stored in a node information table.

[0024] Then, based on the designed laying direction of each cable, the order of the key points that the cable passes through from the starting point to the ending point is determined. The starting point of the cable is the key point where the terminal of the starting device to which the cable is connected is located, and the ending point of the cable is the key point where the terminal of the terminating device to which the cable is connected is located. According to the laying order of the cable from the starting point to the ending point, the path segment between two adjacent key points is determined as a directed edge, and the direction of the directed edge is consistent with the forward direction of the cable laying.

[0025] Each directed edge is assigned a unique directed edge identifier, which is represented in the format of node identifier pairs. For example, the directed edge between the critical location point with node identifier 1 and the critical location point with node identifier 2 is denoted as (1, 2). At the same time, the actual path length of the cable trench or conduit between adjacent critical location points is obtained from the path length annotation of the design drawings and used as the path length value of the corresponding directed edge. The directed edge identifier, starting node identifier, ending node identifier and path length value of each directed edge are stored in a directed edge information table.

[0026] Finally, the node information table and the directed edge information table are combined to construct a directed topology graph. The directed topology graph uses all key location points as nodes and all path segments between adjacent key location points as directed edges. Each directed edge has a clear direction and path length value.

[0027] Step S102: During the laying operation, environmental sensors installed at multiple preset monitoring points continuously collect time-series data reflecting the construction dynamics near each preset monitoring point.

[0028] In this step, multiple pre-set monitoring points are deployed at the construction site in the area to be laid. The deployment locations of these monitoring points include: one monitoring point at each critical location point, and one monitoring point at the midpoint of each directed edge. The monitoring points at critical locations are installed on the sidewalls of the cable trench, the walls of the shaft, the walls near the distribution cabinet, or on supports near the terminal boxes. The monitoring points at the midpoints of the directed edges are installed at the bottom of the cable trench or in the middle of the cable channel. Each frame of time-series data includes: monitoring point identifier, acquisition timestamp, sound intensity value, and vibration intensity value.

[0029] Step S103: Associate each directed edge in the directed topology graph with the spatial locations of at least two preset monitoring points to establish a mapping relationship between the directed edges and the preset monitoring points.

[0030] In this step, the installation location coordinates of each of the preset monitoring points are obtained; For each directed edge in the laid directed topology graph, obtain the coordinates of the starting node and the ending node of the directed edge; Calculate the first set of Euclidean distances between the installation location coordinates of all preset monitoring points and the coordinates of the starting node, and select the preset monitoring point corresponding to the smallest first Euclidean distance in the first set of Euclidean distances as the first associated monitoring point; Calculate the second set of Euclidean distances between the installation location coordinates of all preset monitoring points and the coordinates of the endpoint node, and select the preset monitoring point corresponding to the smallest second Euclidean distance in the second set of Euclidean distances as the second associated monitoring point; The monitoring point identifiers of the first associated monitoring point and the second associated monitoring point are associated and stored with the directed edge identifier of the directed edge to obtain the mapping relationship.

[0031] In one specific embodiment, the installation location coordinates of each preset monitoring point are first obtained. After the monitoring points are deployed, the construction personnel use a total station or a handheld laser rangefinder to accurately measure the actual installation location of each preset monitoring point, and obtain the three-dimensional spatial coordinates of each monitoring point in the construction coordinate system. The monitoring point identifier of each monitoring point is associated with the measured installation location coordinates and stored in the monitoring point location table of the background data processing server. The installation location coordinates of the monitoring point are represented by three values: horizontal coordinate, vertical coordinate and elevation.

[0032] Then, for each directed edge in the directed topology graph, perform the following association operation: The first step is to obtain the coordinates of the starting node and the ending node of the directed edge. The node identifier of the starting node is read from the node information table, and the spatial coordinates of the starting node are queried based on the node identifier. Similarly, the spatial coordinates of the ending node are read. The second step is to calculate the first Euclidean distance between the installation location coordinates of all preset monitoring points and the coordinates of the starting node, and to form a set of first Euclidean distances corresponding to all monitoring points. The third step is to traverse all distance values ​​in the first Euclidean distance set, find the minimum value among them, i.e. the minimum first Euclidean distance, determine the preset monitoring point corresponding to the minimum first Euclidean distance, and use the preset monitoring point as the first associated monitoring point of the directed edge. The fourth step is to calculate the second Euclidean distance between the installation location coordinates of all preset monitoring points and the coordinates of the endpoint node, and to form a set of second Euclidean distances corresponding to all monitoring points.

[0033] Fifth step: Traverse all distance values ​​in the second Euclidean distance set, find the minimum value, i.e. the minimum second Euclidean distance, determine the preset monitoring point corresponding to the minimum second Euclidean distance, and use the preset monitoring point as the second associated monitoring point of the directed edge; Step 6: Associate the monitoring point identifiers of the first and second associated monitoring points with the directed edge identifier of the directed edge, and store the association records to obtain a mapping record. This mapping record contains four fields: directed edge identifier, first associated monitoring point identifier, second associated monitoring point identifier, and association establishment timestamp. Store this mapping record in the mapping relationship table of the backend data processing server. For each directed edge in the directed topology graph, perform the operations from step one to step six above. After traversal, the mapping table stores the mapping relationship records between all directed edges and preset monitoring points. Each directed edge is associated with at least two preset monitoring points, namely, one monitoring point closest to the starting node and one monitoring point closest to the ending node.

[0034] The above steps automatically establish a mapping relationship between directed edges and monitoring points through spatial nearest neighbor matching, achieving the following technical effects: Using spatial Euclidean distance as the basis for association, it is ensured that the monitoring point associated with each directed edge is the monitoring point with the closest spatial distance to the start and end points of the directed edge. This enables the time series data collected by the monitoring points to most accurately reflect the construction dynamics of the area near the directed edge, avoiding distance deviations or coverage blind spots that may be caused by manually specifying monitoring points. Each directed edge is associated with at least two monitoring points, located at the starting and ending points of the directed edge respectively. This dual-end coverage method can simultaneously sense construction activities from two different locations, providing multi-angle sound and vibration sensing data for subsequent construction action recognition, and enhancing the robustness and accuracy of action recognition. The establishment of mapping relationships is fully automated, eliminating the need for construction management personnel to manually configure the correspondence between directed edges and monitoring points one by one, reducing the possibility of human error and improving the system's deployment efficiency.

[0035] Step S104: For each cable, obtain the wireless signal emitted by the wireless beacon attached to the cable end at a preset time interval, receive the wireless signal through the signal receiver set at each of the key locations, determine the path segment at each time point of the cable end based on the signal strength indication value of the received signal, and generate the directed edge sequence that the cable end has been traversed.

[0036] In this step, the wireless beacon is a Bluetooth Low Energy beacon, the signal receiver is a Bluetooth Low Energy gateway, and the wireless beacon broadcasts a broadcast packet containing a cable identifier at a preset time interval with a fixed transmission power.

[0037] Each of the signal receivers receives the broadcast packet, extracts the cable identifier contained in the broadcast packet, measures the signal strength indicator value of the received signal, and packages the cable identifier, the signal strength indicator value, and the reception time into a reporting data packet; For each reporting time, based on the signal strength indication values ​​of the same cable identifier at at least three signal receivers, a preset logarithmic distance path loss model is used to convert each signal strength indication value into an estimated distance from the wireless beacon to each signal receiver. Based on the estimated distance and the known installation coordinates of each signal receiver, the weighted centroid positioning algorithm is used to calculate the estimated position coordinates of the wireless beacon at the reporting time. The estimated location coordinates are matched with the known coordinates of each key location point in the directed topology map to determine the key location point closest to the cable head at the reporting time. Determine the path segment containing the nearest critical location point as the path segment where the cable's head end is located at the reporting time; Arrange the path segments determined at each time point in chronological order, merge adjacent and repeated path segments, and obtain the directed edge sequence that has been traversed at the beginning of the cable.

[0038] In one specific embodiment, a wireless beacon is first fixedly installed at the beginning of each secondary cable to be laid. The wireless beacon is a Bluetooth Low Energy (BLE) beacon, and each BLE beacon stores a unique beacon identifier. This beacon identifier is bound one-to-one with the cable identifier of the cable to be laid, and the binding relationship table is pre-stored in the background data processing server. The transmission power of the Bluetooth Low Energy beacon is fixed at 0 dB / mW, and the broadcast interval is 100 milliseconds, that is, a broadcast packet is transmitted every 100 milliseconds. The broadcast packet contains the beacon identifier field, and the background server can obtain the corresponding cable identifier by querying the binding relationship table.

[0039] Before the laying operation begins, signal receivers are installed at each key location. The signal receivers are Bluetooth Low Energy gateways. Each Bluetooth Low Energy gateway has a unique gateway identifier and its own installation location coordinates are known. The installation location coordinates of the Bluetooth Low Energy gateways are measured by the construction personnel using a laser rangefinder during installation and are pre-entered into the background data processing server.

[0040] Once the laying operation begins, the cable is pulled forward, and the Bluetooth Low Energy beacon fixed at the beginning of the cable moves with the cable in the cable trench or pipe, continuously broadcasting a broadcast packet containing the beacon identification code at 100-millisecond intervals. The Bluetooth Low Energy gateways deployed at each key location are continuously in scanning mode. When the Bluetooth Low Energy gateway is within the effective communication range of the Bluetooth Low Energy beacon, the Bluetooth Low Energy gateway receives the broadcast packet.

[0041] After receiving a broadcast packet, the Bluetooth Low Energy gateway performs the following processing: extracts the beacon identification code from the broadcast packet; measures the signal strength indicator value of the received signal, with the unit of the signal strength indicator value being decibels and milliwatts; records the reception time; packages the beacon identification code, signal strength indicator value, and reception time into a reporting data packet; and sends the reporting data packet to the background data processing server in real time through the communication network.

[0042] After receiving all the reported data packets from Bluetooth Low Energy gateways, the backend data processing server processes them in real time. The server queries the binding relationship table based on the beacon identification code to obtain the corresponding cable identifier, thereby determining which cable the reported data packet belongs to.

[0043] For each reporting time, the backend data processing server filters out all reported data packets that are near the same reporting time, within a time window of ±50 milliseconds, and have the same cable identifier. If reported data packets with the same cable identifier near a certain reporting time come from at least three different Bluetooth Low Energy gateways, then location calculation is performed.

[0044] The specific process of location calculation is as follows: For each reported data packet selected, the signal strength indicator value and the corresponding Bluetooth Low Energy (BLE) gateway identifier are extracted. Based on the BLE gateway identifier, the gateway installation location coordinate table is queried to obtain the known installation location coordinates of the BLE gateway. Using a preset logarithmic distance path loss model, each signal strength indicator value is converted into an estimated distance from the BLE beacon to the corresponding BLE gateway. The calculation formula for the logarithmic distance path loss model is: , In the formula, This is the signal strength indication value. This is the reference signal strength indication value at a reference distance of 1 meter. This is the environmental path loss index. This is the estimated distance we are looking for.

[0045] After obtaining the estimated distance from the Bluetooth Low Energy beacon to each Bluetooth Low Energy gateway, the weighted centroid localization algorithm is used to calculate the estimated position coordinates of the Bluetooth Low Energy beacon at the current reporting time.

[0046] After calculating the estimated location coordinates of the Bluetooth Low Energy beacon at the current reporting time, the background data processing server performs spatial nearest neighbor matching between the estimated location coordinates and the known coordinates of each key location point in the directed topology map. The specific method of spatial nearest neighbor matching is as follows: calculate the spatial Euclidean distance between the estimated location coordinates and the coordinates of each key location point, and select the key location point with the smallest spatial Euclidean distance as the key location point closest to the cable head at the reporting time.

[0047] After identifying the nearest critical location, the path segment containing that critical location is located in the directed topology graph. If the critical location is the start or end point of a directed edge, then the path segment containing that critical location is that directed edge. If the critical location is the intersection of multiple directed edges, the designed route of the cable at that intersection is determined based on the cable's designed route data, and the directed edge consistent with the designed route is selected as the path segment containing that critical location. The determined path segment is the path segment where the cable's head end is located at the time of reporting.

[0048] The background data processing server arranges the path segments determined at each reporting time in chronological order to form a path segment time series. Then, it merges adjacent duplicates in the path segment time series, that is, it merges the cases where multiple consecutive times are determined to be the same path segment into one record, and only retains the first and last times the path segment appears. The merged path segment sequence is the directed edge sequence that has been traversed at the beginning of the cable.

[0049] In this embodiment, a logarithmic distance path loss model is used to convert signal strength indication values ​​into distance estimates. Then, a weighted centroid positioning algorithm is used to fuse the ranging results of multiple gateways, achieving meter-level positioning accuracy in complex cable trench and pipeline environments, meeting the spatial resolution requirements for cable laying progress monitoring. The positioning results are then matched with key locations in the directed topology map using spatial nearest neighbor matching. Prior knowledge of the topology map is used to discretize continuous coordinate estimates into clear path segment determinations, avoiding misjudgments of path segments due to positioning errors. At the same time, the discretized path segments are arranged in chronological order and deduplicated, resulting in a concise and physically meaningful directed edge sequence, providing a reliable location benchmark for subsequent construction action identification and progress calculation.

[0050] Step S105: Based on the mapping relationship, extract the time series data of all preset monitoring points associated with a certain directed edge in the directed edge sequence to obtain the target time series data set.

[0051] In this step, based on a directed edge identifier of a directed edge in the directed edge sequence, at least two monitoring point identifiers associated with the directed edge identifier are searched in the mapping relationship to form a target monitoring point identifier set. Based on the start and end times of the cable head appearing on a certain directed edge, a target time period is determined, wherein the start time is the time when the cable head first enters the certain directed edge, and the end time is the time when the cable head first leaves the certain directed edge and enters the next directed edge. From the time-series data collected from all preset monitoring points, extract the time-series data collected by the monitoring point corresponding to each target monitoring point identifier in the target monitoring point identifier set within the target time period. The time-series data includes a sequence of sound intensity sampling points and a sequence of vibration intensity sampling points arranged in order of collection time. The sequence of sound intensity sampling points consists of several sound intensity sampling points, and each sound intensity sampling point contains a sampling time and a sound intensity value. The sequence of vibration intensity sampling points consists of several vibration intensity sampling points, and each vibration intensity sampling point contains a sampling time and a vibration intensity value. The extracted sound intensity sampling point sequences and vibration intensity sampling point sequences of all target monitoring points are grouped according to the monitoring point identifier and aligned according to the sampling time to form the target time series data set.

[0052] In one specific embodiment, for each traversed directed edge in the directed edge sequence, the following data extraction operation is performed one by one to obtain the target time series data set of that directed edge.

[0053] First, based on the directed edge identifier of the current directed edge to be processed, a query is performed in the mapping table. During the query, the directed edge identifier of the current directed edge is used as the query condition. All records matching the directed edge identifier are retrieved from the mapping table, and all monitoring point identifiers stored in these records are extracted to form the target monitoring point identifier set. Since each directed edge is associated with at least two monitoring points, the target monitoring point identifier set contains at least two monitoring point identifiers.

[0054] Then, the target time period for data extraction is determined. The start and end times of the target time period are determined based on the time when the cable head appears on the directed edge. From the directed edge sequence generated in step S104, the record corresponding to the current directed edge is searched. Each record in the directed edge sequence contains a directed edge identifier, an entry time, and a departure time. The entry time is the time when the cable head first enters the directed edge, and the departure time is the time when the cable head first leaves the directed edge and enters the next directed edge. The entry time is taken as the start time of the target time period, and the departure time is taken as the end time of the target time period. If the current directed edge is the last directed edge on the cable design path, and the cable has reached the destination, then the departure time is taken as the time when the cable head reaches the destination.

[0055] After determining the target monitoring point identifier set and the target time period, the background data processing server extracts the required data from the time-series data collected from all preset monitoring points. The specific extraction method is as follows: traverse each monitoring point identifier in the target monitoring point identifier set, and for each monitoring point identifier, extract all data from the time-series data of that monitoring point whose sampling time falls between the start and end times of the target time period, including all sound intensity sampling points and vibration intensity sampling points within that time period. The extracted data forms the sound intensity sampling point sequence and vibration intensity sampling point sequence of that monitoring point.

[0056] Finally, the extracted sound intensity sampling sequence and vibration intensity sampling sequence of all target monitoring points are combined to form a target time-series data set. The specific combination method is as follows: data is grouped according to the monitoring point identifier, meaning that the sound intensity sampling sequence and vibration intensity sampling sequence of each monitoring point are treated as a single data set. Data from different monitoring points are stored independently. Simultaneously, the data from different monitoring points are aligned according to the sampling time, preserving the timestamp information of the original sampling time. This ensures that during subsequent frame-by-frame processing, the index position of the same frame corresponds to data collected by different monitoring points within the same time window. The combined target time-series data set contains at least two data sets, each corresponding to one target monitoring point, and each data set contains one sound intensity sampling sequence and one vibration intensity sampling sequence.

[0057] The above operation is performed on each traversed directed edge in the directed edge sequence, and each directed edge obtains its corresponding target time series data set for subsequent steps to perform action recognition and progress determination.

[0058] In summary, by automatically locating monitoring points associated with directed edge space using pre-established mapping relationships, blind searching within the full monitoring point data is avoided, significantly narrowing the data retrieval range and improving data extraction efficiency. Using the actual dwell time of the cable head on the directed edge as the target time period, precise extraction of time-series data within this time period ensures that the extracted data strictly corresponds to the current laying process of the directed edge in time, eliminating irrelevant noise data generated by other construction activities before the cable arrives or has left, thus improving the signal-to-noise ratio for subsequent action recognition. The extracted time-series data simultaneously includes sound intensity sampling point sequences and vibration intensity sampling point sequences. These two sensing modes capture the airborne sound propagation and solid vibration propagation characteristics of the construction site, respectively. Their complementary physical characteristics allow for a more comprehensive reflection of the acoustic and vibration characteristics of different types of construction actions, providing rich multimodal information for subsequent feature extraction and action classification.

[0059] Step S106: Adaptively divide the target time series data set into multiple action data segments corresponding to a single construction action, determine the construction action type corresponding to each action data segment, and arrange the determined construction action types in chronological order to obtain the actual construction action sequence.

[0060] In this step, the sound intensity sampling point sequence of each monitoring point in the target time series data set is divided into frames with a preset frame length and a preset frame shift. The preset frame length is half of the preset sampling frequency, and the preset frame shift is half of the preset frame length. After framing, each frame of sound intensity data consists of L consecutive sound intensity sampling points in the sound intensity sampling point sequence, where L is equal to the preset frame length. There is an overlap of L / 2 sound intensity sampling points between two adjacent frames of sound intensity data. The vibration intensity sampling point sequence of each monitoring point in the target time series data set is subjected to the same frame segmentation process using the preset frame length and the preset frame shift. After the frame segmentation, each frame of vibration intensity data is composed of L consecutive vibration intensity sampling points in the vibration intensity sampling point sequence. For a frame of sound intensity data at a certain monitoring point, the sound intensity values ​​of the L sound intensity sampling points that make up the frame of sound intensity data are squared and then summed to obtain the short-time energy of the sound at the certain monitoring point for that frame. For a certain frame of vibration intensity data at a certain monitoring point, the vibration intensity values ​​of the L vibration intensity sampling points that make up the certain frame of vibration intensity data are squared and then summed to obtain the short-time vibration energy of the certain monitoring point in that frame. The average sound short-time energy sequence is obtained by averaging the short-time sound energy of all monitoring points at the same frame index, and the average vibration short-time energy sequence is obtained by averaging the short-time vibration energy of all monitoring points at the same frame index. Multiply the average sound short-time energy sequence by the value at the same frame index in the average vibration short-time energy sequence to obtain the fused energy sequence; In the fused energy sequence, consecutive frame index intervals with fused energy values ​​lower than a preset mute threshold are marked as mute intervals, and frame index intervals between two adjacent mute intervals are marked as active intervals. Using the start frame index and end frame index of each activity interval as boundaries, the time series data of all monitoring points in the target time series data set are divided into multiple data segments, each data segment corresponding to one action data segment.

[0061] Furthermore, for each action data segment, sound time-domain features and sound frequency domain features are extracted from the sound intensity sampling point sequence of each monitoring point in the action data segment, and vibration time-domain features and vibration frequency domain features are extracted from the vibration intensity sampling point sequence of each monitoring point. The temporal characteristics of sound include the mean and variance of the short-time zero-crossing rate and the mean and variance of the short-time energy. The short-time zero-crossing rate is the ratio of the number of times the sign of the sound intensity value changes between two adjacent sampling points in the sound intensity sampling point sequence to the total number of sampling points. It is calculated as follows: traverse all sound intensity sampling points of a certain monitoring point within the action data segment, count the number of times the sign of the sound intensity value changes between two adjacent sampling points, divide this number by the total number of sampling points minus one, and obtain the mean of the short-time zero-crossing rate of the sound at that monitoring point within the action data segment; the short-time energy is the mean of the sum of the squares of the sound intensity values ​​of all sampling points in the sound intensity sampling point sequence. Vibration time-domain characteristics include the maximum and mean values ​​of vibration peak values ​​and vibration effective values. Vibration peak values ​​refer to the maximum values ​​of vibration intensity values ​​in the vibration intensity sampling point sequence, and vibration effective values ​​refer to the square root of the mean of the sum of squares of vibration intensity values ​​at all sampling points in the vibration intensity sampling point sequence. The sound time-domain features, sound frequency domain features, vibration time-domain features, and vibration frequency domain features of each monitoring point are concatenated into a motion feature vector in a preset order; The preset order is as follows: first arrange all features of the first monitoring point, then arrange all features of the second monitoring point, and so on, until all features of all monitoring points are arranged. After concatenation, a one-dimensional vector is obtained, which serves as the action feature vector of the action data segment. Obtain a preset construction action feature library, which stores multiple standard action feature vectors. Each standard action feature vector is pre-associated with a type of construction action, including cable pulling action, cable binding action, cable bending and adjustment action, cover plate opening and closing action, and personnel walking action. Calculate the cosine similarity between the action feature vector and each standard action feature vector, and select the construction action type associated with the standard action feature vector corresponding to the maximum cosine similarity as the construction action type corresponding to the action data segment; The construction action types corresponding to each action data segment are arranged sequentially according to the chronological order of the action data segments to obtain the actual construction action sequence.

[0062] In summary, using the fusion of sound and vibration energy as the segmentation basis, multiplying the energy of the two physical modes instead of simply adding them, makes the segmentation more sensitive to construction activities that simultaneously generate sound and vibration, while naturally suppressing environmental interference that only generates single-mode noise. When there is sudden single-mode noise in the environment, the fusion energy value is suppressed because the energy of the other mode is lower, making it less likely to be misjudged as a construction activity area, thus improving the accuracy of activity area identification. Adaptive segmentation with a silence threshold replaces fixed-duration segmentation, and the segmentation boundary is completely determined by the natural start and end of the construction activity. The length of the data segment corresponding to different construction actions can be flexibly changed, neither mechanically splitting a complete action nor forcibly merging multiple actions, ensuring the physical integrity of the action data segment. The half-frame overlapping framing method, with 50% overlap between adjacent frames, ensures the smooth continuity of the energy sequence in time, avoids missegmentation caused by energy abrupt changes at frame boundaries, and improves the temporal resolution to the frame shift level, enabling precise capture of the start and end boundaries of construction actions.

[0063] Step S107: Compare the actual construction action sequence with the preset standard action sequence template for laying procedures. If the matching degree exceeds the preset procedure completion threshold, the path length value of a certain directed edge is added to the laid length of the cable. The laid length is then divided by the total designed path length of the cable to obtain the laying progress of the cable.

[0064] In this step, a preset standard action sequence template for laying procedures corresponding to a certain directed edge is obtained. The standard action sequence template for laying procedures defines the sequence of standard construction action types that need to be executed sequentially to complete the cable laying of the certain directed edge. Construct a cumulative distance matrix between the actual construction action sequence and the standard action sequence template for the laying process. The element value in the i-th row and j-th column of the cumulative distance matrix is: the single action distance between the i-th construction action type in the actual construction action sequence and the j-th standard construction action type in the standard action sequence template for the laying process, plus the minimum value among the three elements in the (i-1)-th row and j-th column of the cumulative distance matrix. If the i-th construction action type is the same as the j-th standard construction action type, the single action distance is zero; if they are different, the single action distance is one. The minimum cumulative distance is taken as the element value at the bottom right corner of the cumulative distance matrix, and the reciprocal of the minimum cumulative distance is taken as the matching degree. If the matching degree is greater than the preset process completion threshold, it is determined that the cable laying of a certain directed edge has been completed. The path length value of the certain directed edge is obtained from the laying directed topology graph, and the path length value is added to the laid length of the cable. For each traversed directed edge in the directed edge sequence, perform the above sequence comparison and accumulation operation one by one. Divide the laid length of the cable obtained after traversal by the total designed path length of the cable to obtain the laying progress of the cable.

[0065] In one specific embodiment, a preset standard action sequence template for laying procedures corresponding to the directed edge to be determined is first obtained. Before the laying operation begins, the standard action sequence template for laying procedures is pre-compiled by construction technical management personnel according to construction process specifications and standard operating procedures and stored in the template library of the background data processing server. Each standard action sequence template for laying procedures corresponds to a type of directed edge. The type of directed edge is divided according to the construction environment characteristics of the path segment where the directed edge is located, including five types: horizontal cable trench segment, cable trench turning segment, vertical shaft segment, conduit segment, and terminal wiring segment.

[0066] The standard action sequence template for cable laying procedures is an ordered sequence of standard construction action types, defining the standard construction actions to be performed sequentially to complete the laying of cables on a directed side of the corresponding type. For example, the standard action sequence template for laying cables in a horizontal section of a cable trench is: "Personnel movement, cover opening and closing, cable pulling, cable bending and adjustment, cable binding, cover opening and closing, personnel movement." The standard action sequence template for laying cables in a turning section of a cable trench is: "Personnel movement, cover opening and closing, cable pulling, cable bending and adjustment, cable bending and adjustment, cable binding, cover opening and closing, personnel movement." The standard action sequence template for laying cables in a vertical section of a shaft is: "Personnel movement, cable pulling, cable pulling, cable binding, personnel movement." In each type of standard action sequence template, the order and frequency of the standard construction action types are determined according to the actual sequence of construction procedures.

[0067] For the directed edge to be determined, the type of the directed edge is determined based on the attribute information of the directed edge in the laying directed topology graph, and then the standard action sequence template of the laying procedure that matches the type is retrieved from the template library.

[0068] Then, a cumulative distance matrix is ​​constructed between the actual construction action sequence and the standard action sequence template for the laying procedure. Let the length of the actual construction action sequence be *m*, meaning it contains *m* construction action types. Let the length of the standard action sequence template for the laying procedure be *n*, meaning it contains *n* standard construction action types. The cumulative distance matrix is ​​an *m* x *n* two-dimensional matrix. The row indices *i* from 1 to *m* correspond to the 1st to *m*th construction action types in the actual construction action sequence. The column indices *j* from 1 to *n* correspond to the 1st to *n*th standard construction action types in the standard action sequence template for the laying procedure.

[0069] The cumulative distance matrix is ​​filled using a dynamic programming algorithm, calculating the value of each matrix element row by row and column by column, starting from row 1 and column 1. For the element D(i,j) in row i and column j, the calculation method is as follows: First, determine the distance between the i-th construction action type in the actual construction action sequence and the j-th standard construction action type in the standard action sequence template for the laying procedure. If the i-th construction action type and the j-th standard construction action type are the same, for example, both are "cable pulling action", then the distance between the two is zero. If the i-th construction action type and the j-th standard construction action type are different, for example, the i-th is "cable pulling action" while the j-th is "cable binding action", then the distance between the two is one.

[0070] Then determine the values ​​of three adjacent matrix elements. When i is greater than 1 and j is greater than 1, the three adjacent elements are D(i-1,j), D(i,j-1), and D(i-1,j-1). When i equals 1 and j equals 1, there are no adjacent elements, so the single action distance is directly taken as the value of D(1,1). When i equals 1 and j is greater than 1, only the left adjacent element D(1,j-1) exists. When i is greater than 1 and j equals 1, only the upper adjacent element D(i-1,1) exists. Take the minimum value among all existing adjacent elements, add the single action distance to this minimum value, and obtain the value of D(i,j).

[0071] Calculate row by row and column by column in the manner described above until all elements of the entire cumulative distance matrix are filled.

[0072] After calculation, the element value at the bottom right corner of the cumulative distance matrix, i.e., the element value D(m,n) in the m-th row and n-th column, is taken as the minimum cumulative distance between the actual construction action sequence and the standard action sequence template for the laying procedure. The minimum cumulative distance represents the minimum editing cost required to convert the actual construction action sequence into the standard action sequence template for the laying procedure through insertion, deletion, or replacement operations.

[0073] The reciprocal of the minimum cumulative distance is used as the matching degree, i.e. The matching degree ranges from 0 to 1. The higher the matching degree, the higher the similarity between the actual construction action sequence and the standard action sequence template of the laying procedure, that is, the closer the actual construction action is to the standard procedure requirements.

[0074] The calculated matching degree is compared with a preset process completion threshold. The preset process completion threshold is determined based on statistical analysis of historical construction data and is set to 0.5. If the matching degree is greater than 0.5, the cable laying of the current directed edge is considered complete. The path length value of the current directed edge is queried from the directed topology graph and added to the laid cable length. The initial value of the laid length is zero, and the path length value is added to the total laid length of each directed edge that is confirmed to be completed.

[0075] If the matching degree is not greater than 0.5, it is determined that the cable laying of the current directed edge is not completed, and the path length value of the current directed edge is not added to the cable laying length.

[0076] For each directed edge in the directed edge sequence that has been traversed at the beginning of the cable, perform the above sequence comparison and accumulation operations one by one. The traversal order follows the arrangement order of each directed edge in the directed edge sequence, that is, the time sequence in which the beginning of the cable passes through each directed edge.

[0077] After traversing the network, the laid cable length is obtained. This laid length is then divided by the total designed path length, which is the sum of the path lengths of all directed edges the cable traverses from its starting point to its ending point. This total designed path length is directly obtained from the directed topology graph. The division yields a ratio between 0 and 1. Multiplying this ratio by 100% gives the cable laying progress, expressed as a percentage.

[0078] In summary, the method of this application constructs a directed topology graph for cable laying; collects construction sound and vibration time-series data through environmental sensors and establishes a mapping relationship between directed edges and monitoring points; utilizes wireless beacons at the cable ends for positioning to generate a sequence of traversed directed edges; extracts the target time-series data set, adaptively segments it into action data segments, identifies the types of construction actions, and forms an actual construction action sequence; dynamically time-normalizes and compares the actual action sequence with a preset standard action sequence template for laying procedures; if the matching degree exceeds a threshold, the corresponding path length is accumulated to calculate the laying progress; by fusing multi-source sound and vibration data, adaptive action segmentation, and sequence comparison, real-time, automatic progress monitoring without relying on manual recording is achieved, solving the problems of lag and error susceptibility in traditional manual recording, and significantly improving the accuracy and timeliness of power engineering cable laying progress management. Please see Figure 2 The diagram shows a structural block diagram of a secondary cable laying progress monitoring system according to this application.

[0079] like Figure 2 As shown, the secondary cable laying progress monitoring system 200 includes a construction module 210, an acquisition module 220, an association module 230, a generation module 240, an extraction module 250, a segmentation module 260, and an accumulation module 270.

[0080] The system includes a construction module 210, configured to acquire design path data of all secondary cables in the area to be laid, and construct a directed topology map, wherein key locations on the cable laying path are nodes, and path segments between adjacent key locations are directed edges; an acquisition module 220, configured to continuously collect time-series data reflecting the construction dynamics near each preset monitoring point during the laying operation using environmental sensors set at multiple preset monitoring points; an association module 230, configured to associate each directed edge in the directed topology map with the spatial locations of at least two preset monitoring points, establishing a mapping relationship between directed edges and preset monitoring points; and a generation module 240, configured to acquire, for each cable, the wireless signal emitted by the wireless beacon attached to the cable head at preset time intervals, receive the wireless signal through signal receivers set at each of the key locations, and determine the cable head based on the signal strength indication value of the received signal. The system generates a sequence of directed edges that have been traversed at the beginning of the cable, based on the path segment at each moment. An extraction module 250 is configured to extract time-series data of all preset monitoring points associated with a directed edge in the directed edge sequence, according to the mapping relationship, to obtain a target time-series data set. A segmentation module 260 is configured to adaptively segment the target time-series data set into multiple action data segments corresponding to a single construction action, determine the type of construction action corresponding to each action data segment, and arrange the determined construction action types in chronological order to obtain an actual construction action sequence. An accumulation module 270 is configured to compare the actual construction action sequence with a preset standard action sequence template for laying procedures. If the matching degree exceeds a preset procedure completion threshold, the path length value of a directed edge is accumulated into the already laid length of the cable, and the already laid length is divided by the total designed path length of the cable to obtain the laying progress of the cable.

[0081] It should be understood that Figure 2 The modules and references described in the document Figure 1 The steps described in the text correspond to those in the method described above. Therefore, the operations, features, and corresponding technical effects described above also apply to the method described in the text. Figure 2 The various modules in the document will not be described in detail here.

[0082] In other embodiments, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor performs the secondary cable laying progress monitoring method in any of the above method embodiments. In one embodiment, the computer-readable storage medium of the present invention stores computer-executable instructions, which are configured as follows: Obtain the design path data of all secondary cables in the area to be laid, and construct a directed topology graph. The directed topology graph uses key locations on the cable laying path as nodes and path segments between adjacent key locations as directed edges. During the laying operation, environmental sensors installed at multiple preset monitoring points continuously collect time-series data reflecting the construction dynamics near each preset monitoring point. Each directed edge in the laid directed topology graph is associated with the spatial location of at least two preset monitoring points to establish a mapping relationship between the directed edge and the preset monitoring points. For each cable, the wireless signal emitted by the wireless beacon attached to the cable end at a preset time interval is obtained, the wireless signal is received by the signal receiver set at each of the key locations, and the path segment at each time point of the cable end is determined according to the signal strength indication value of the received signal, and the directed edge sequence that the cable end has been traversed is generated. Based on the mapping relationship, extract the time series data of all preset monitoring points associated with a certain directed edge in the directed edge sequence to obtain the target time series data set; The target time series data set is adaptively divided into multiple action data segments corresponding to a single construction action, and the construction action type corresponding to each action data segment is determined. The construction action types determined in sequence are arranged in chronological order to obtain the actual construction action sequence. The actual construction action sequence is compared with the preset standard action sequence template for laying procedures. If the matching degree exceeds the preset procedure completion threshold, the path length value of a certain directed edge is added to the laid length of the cable. The laid length is then divided by the total designed path length of the cable to obtain the laying progress of the cable.

[0083] Computer-readable storage media may include a stored program area and a stored data area, wherein the stored program area may store an operating system and an application program required for at least one function; the stored data area may store data created based on the use of the secondary cable laying progress monitoring system, etc. Furthermore, the computer-readable storage medium may include high-speed random access memory, and may also include memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the computer-readable storage medium may optionally include memory remotely disposed relative to a processor, and this remote memory may be connected to the secondary cable laying progress monitoring system via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0084] Figure 3 This is a schematic diagram of the structure of the electronic device provided in the embodiment of the present invention, such as... Figure 3 As shown, the device includes a processor 310 and a memory 320. The electronic device may also include an input device 330 and an output device 340. The processor 310, memory 320, input device 330, and output device 340 can be connected via a bus or other means. Figure 3 Taking a bus connection as an example, the memory 320 is the computer-readable storage medium described above. The processor 310 executes various server functions and data processing by running non-volatile software programs, instructions, and modules stored in the memory 320, thereby implementing the secondary cable laying progress monitoring method described in the above embodiment. The input device 330 can receive input digital or character information and generate key signal inputs related to user settings and function control of the secondary cable laying progress monitoring system. The output device 340 may include a display screen or other display device.

[0085] The aforementioned electronic device can execute the method provided in the embodiments of the present invention, and has the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in this embodiment can be found in the method provided in the embodiments of the present invention.

[0086] In one implementation, the above-described electronic device is applied to a secondary cable laying progress monitoring system for a client, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to: Obtain the design path data of all secondary cables in the area to be laid, and construct a directed topology graph. The directed topology graph uses key locations on the cable laying path as nodes and path segments between adjacent key locations as directed edges. During the laying operation, environmental sensors installed at multiple preset monitoring points continuously collect time-series data reflecting the construction dynamics near each preset monitoring point. Each directed edge in the laid directed topology graph is associated with the spatial location of at least two preset monitoring points to establish a mapping relationship between the directed edge and the preset monitoring points. For each cable, the wireless signal emitted by the wireless beacon attached to the cable end at a preset time interval is obtained, the wireless signal is received by the signal receiver set at each of the key locations, and the path segment at each time point of the cable end is determined according to the signal strength indication value of the received signal, and the directed edge sequence that the cable end has been traversed is generated. Based on the mapping relationship, extract the time series data of all preset monitoring points associated with a certain directed edge in the directed edge sequence to obtain the target time series data set; The target time series data set is adaptively divided into multiple action data segments corresponding to a single construction action, and the construction action type corresponding to each action data segment is determined. The construction action types determined in sequence are arranged in chronological order to obtain the actual construction action sequence. The actual construction action sequence is compared with the preset standard action sequence template for laying procedures. If the matching degree exceeds the preset procedure completion threshold, the path length value of a certain directed edge is added to the laid length of the cable. The laid length is then divided by the total designed path length of the cable to obtain the laying progress of the cable.

[0087] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of various embodiments or some parts of embodiments.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring the progress of secondary cable laying, characterized in that, include: Obtain the design path data of all secondary cables in the area to be laid, and construct a directed topology graph. The directed topology graph uses key locations on the cable laying path as nodes and path segments between adjacent key locations as directed edges. During the laying operation, environmental sensors installed at multiple preset monitoring points continuously collect time-series data reflecting the construction dynamics near each preset monitoring point. Each directed edge in the laid directed topology graph is associated with the spatial location of at least two preset monitoring points to establish a mapping relationship between the directed edge and the preset monitoring points. For each cable, the wireless signal emitted by the wireless beacon attached to the cable end at a preset time interval is obtained, and the wireless signal is received by the signal receiver set at each of the key locations. Based on the signal strength indication value of the received signal, the path segment where the cable end is located at each time is determined, and the directed edge sequence that the cable end has been traversed is generated. The wireless beacon is a Bluetooth Low Energy beacon, the signal receiver is a Bluetooth Low Energy gateway, and the wireless beacon broadcasts a broadcast packet containing the cable identifier at a preset time interval with a fixed transmission power. Generating the directed edge sequence specifically includes: Each of the signal receivers receives the broadcast packet, extracts the cable identifier contained in the broadcast packet, measures the signal strength indicator value of the received signal, and packages the cable identifier, the signal strength indicator value, and the reception time into a reporting data packet; For each reporting time, based on the signal strength indication values ​​of the same cable identifier at at least three signal receivers, a preset logarithmic distance path loss model is used to convert each signal strength indication value into an estimated distance from the wireless beacon to each signal receiver. Based on the estimated distance and the known installation coordinates of each signal receiver, the weighted centroid positioning algorithm is used to calculate the estimated position coordinates of the wireless beacon at the reporting time. The estimated location coordinates are matched with the known coordinates of each key location point in the directed topology map to determine the key location point closest to the cable head at the reporting time. Determine the path segment containing the nearest critical location point as the path segment where the cable's head end is located at the reporting time; Arrange the path segments determined at each time point in chronological order, merge adjacent and repeated path segments, and obtain the directed edge sequence that has been traversed at the beginning of the cable. Based on the mapping relationship, extract the time series data of all preset monitoring points associated with a certain directed edge in the directed edge sequence to obtain the target time series data set; The target time series data set is adaptively divided into multiple action data segments corresponding to a single construction action, and the construction action type corresponding to each action data segment is determined. The construction action types determined in sequence are arranged in chronological order to obtain the actual construction action sequence. The actual construction action sequence is compared with the preset standard action sequence template for laying procedures. If the matching degree exceeds the preset procedure completion threshold, the path length value of a certain directed edge is added to the laid length of the cable. The laid length is then divided by the total designed path length of the cable to obtain the laying progress of the cable.

2. The method for monitoring the progress of secondary cable laying according to claim 1, characterized in that, The step of associating each directed edge in the laid directed topology graph with the spatial locations of at least two preset monitoring points to establish a mapping relationship between the directed edges and the preset monitoring points includes: Obtain the installation location coordinates of each of the preset monitoring points; For each directed edge in the laid directed topology graph, obtain the coordinates of the starting node and the ending node of the directed edge; Calculate the first set of Euclidean distances between the installation location coordinates of all preset monitoring points and the coordinates of the starting node, and select the preset monitoring point corresponding to the smallest first Euclidean distance in the first set of Euclidean distances as the first associated monitoring point; Calculate the second set of Euclidean distances between the installation location coordinates of all preset monitoring points and the coordinates of the endpoint node, and select the preset monitoring point corresponding to the smallest second Euclidean distance in the second set of Euclidean distances as the second associated monitoring point; The monitoring point identifiers of the first associated monitoring point and the second associated monitoring point are associated and stored with the directed edge identifier of the directed edge to obtain the mapping relationship.

3. The method for monitoring the progress of secondary cable laying according to claim 1, characterized in that, The step of extracting time-series data of all preset monitoring points associated with a certain directed edge in the directed edge sequence according to the mapping relationship, to obtain the target time-series data set includes: Based on a directed edge identifier of a directed edge in the directed edge sequence, at least two monitoring point identifiers associated with the directed edge identifier are searched in the mapping relationship to form a target monitoring point identifier set. Based on the start and end times of the cable head appearing on a certain directed edge, a target time period is determined, wherein the start time is the time when the cable head first enters the certain directed edge, and the end time is the time when the cable head first leaves the certain directed edge and enters the next directed edge. From the time-series data collected from all preset monitoring points, extract the time-series data collected by the monitoring point corresponding to each target monitoring point identifier in the target monitoring point identifier set within the target time period. The time-series data includes a sequence of sound intensity sampling points and a sequence of vibration intensity sampling points arranged in order of collection time. The sequence of sound intensity sampling points consists of several sound intensity sampling points, and each sound intensity sampling point contains a sampling time and a sound intensity value. The sequence of vibration intensity sampling points consists of several vibration intensity sampling points, and each vibration intensity sampling point contains a sampling time and a vibration intensity value. The extracted sound intensity sampling point sequences and vibration intensity sampling point sequences of all target monitoring points are grouped according to the monitoring point identifier and aligned according to the sampling time to form the target time series data set.

4. The method for monitoring the progress of secondary cable laying according to claim 3, characterized in that, The step of adaptively dividing the target time-series data set into multiple action data segments corresponding to a single construction action includes: The sound intensity sampling point sequence of each monitoring point in the target time series data set is divided into frames with a preset frame length and a preset frame shift. The preset frame length is half of the preset sampling frequency, and the preset frame shift is half of the preset frame length. After framing, each frame of sound intensity data consists of L consecutive sound intensity sampling points in the sound intensity sampling point sequence, where L is equal to the preset frame length. There is an overlap of L / 2 sound intensity sampling points between two adjacent frames of sound intensity data. The vibration intensity sampling point sequence of each monitoring point in the target time series data set is subjected to the same frame segmentation process using the preset frame length and the preset frame shift. After the frame segmentation, each frame of vibration intensity data is composed of L consecutive vibration intensity sampling points in the vibration intensity sampling point sequence. For a frame of sound intensity data at a certain monitoring point, the sound intensity values ​​of the L sound intensity sampling points that make up the frame of sound intensity data are squared and then summed to obtain the short-time energy of the sound at the certain monitoring point for that frame. For a certain frame of vibration intensity data at a certain monitoring point, the vibration intensity values ​​of the L vibration intensity sampling points that make up the certain frame of vibration intensity data are squared and then summed to obtain the short-time vibration energy of the certain monitoring point in that frame. The average sound short-time energy sequence is obtained by averaging the short-time sound energy of all monitoring points at the same frame index, and the average vibration short-time energy sequence is obtained by averaging the short-time vibration energy of all monitoring points at the same frame index. Multiply the average sound short-time energy sequence by the value at the same frame index in the average vibration short-time energy sequence to obtain the fused energy sequence; In the fused energy sequence, consecutive frame index intervals with fused energy values ​​lower than a preset mute threshold are marked as mute intervals, and frame index intervals between two adjacent mute intervals are marked as active intervals. Using the start frame index and end frame index of each activity interval as boundaries, the time series data of all monitoring points in the target time series data set are divided into multiple data segments, each data segment corresponding to one action data segment.

5. The method for monitoring the progress of secondary cable laying according to claim 1, characterized in that, The step of determining the construction action type corresponding to each action data segment and arranging the determined construction action types in chronological order to obtain the actual construction action sequence includes: For each action data segment, sound time-domain features and sound frequency domain features are extracted from the sound intensity sampling point sequence of each monitoring point in the action data segment, and vibration time-domain features and vibration frequency domain features are extracted from the vibration intensity sampling point sequence of each monitoring point. The sound time-domain features, sound frequency domain features, vibration time-domain features, and vibration frequency domain features of each monitoring point are concatenated into a motion feature vector in a preset order; Obtain a preset construction action feature library, which stores multiple standard action feature vectors. Each standard action feature vector is pre-associated with a type of construction action, including cable pulling action, cable binding action, cable bending and adjustment action, cover plate opening and closing action, and personnel walking action. Calculate the cosine similarity between the action feature vector and each standard action feature vector, and select the construction action type associated with the standard action feature vector corresponding to the maximum cosine similarity as the construction action type corresponding to the action data segment; The construction action types corresponding to each action data segment are arranged sequentially according to the chronological order of the action data segments to obtain the actual construction action sequence.

6. The method for monitoring the progress of secondary cable laying according to claim 1, characterized in that, The step of comparing the actual construction action sequence with the preset standard action sequence template for laying procedures, and if the matching degree exceeds the preset procedure completion threshold, then the path length value of a certain directed edge is added to the already laid length of the cable, and the laid length is divided by the total designed path length of the cable to obtain the cable laying progress includes: Obtain a preset standard action sequence template for laying procedures corresponding to a certain directed edge. The standard action sequence template for laying procedures defines a sequence of standard construction action types that need to be executed sequentially to complete the laying of cables on the certain directed edge. Construct a cumulative distance matrix between the actual construction action sequence and the standard action sequence template of the laying procedure; The minimum cumulative distance is taken as the element value at the bottom right corner of the cumulative distance matrix, and the reciprocal of the minimum cumulative distance is taken as the matching degree. If the matching degree is greater than the preset process completion threshold, it is determined that the cable laying of a certain directed edge has been completed. The path length value of the certain directed edge is obtained from the laying directed topology graph, and the path length value is added to the laid length of the cable. For each traversed directed edge in the directed edge sequence, perform the above sequence comparison and accumulation operation one by one. Divide the laid length of the cable obtained after traversal by the total designed path length of the cable to obtain the laying progress of the cable.

7. A secondary cable laying progress monitoring system, characterized in that, include: The construction module is configured to obtain the design path data of all secondary cables in the area to be laid, and construct a directed topology graph for laying. The directed topology graph for laying uses key location points on the cable laying path as nodes and path segments between adjacent key location points as directed edges. The acquisition module is configured to continuously collect time-series data reflecting the construction dynamics near each preset monitoring point through environmental sensors set at multiple preset monitoring points during the laying operation. The association module is configured to associate each directed edge in the laid directed topology graph with the spatial positions of at least two preset monitoring points, and establish a mapping relationship between the directed edge and the preset monitoring points. The generation module is configured to, for each cable, acquire the wireless signal emitted by the wireless beacon attached to the cable end at a preset time interval, receive the wireless signal through a signal receiver set at each of the key locations, determine the path segment at each time point of the cable end based on the signal strength indication value of the received signal, and generate a directed edge sequence that has been traversed by the cable end. The wireless beacon is a Bluetooth Low Energy beacon, the signal receiver is a Bluetooth Low Energy gateway, and the wireless beacon broadcasts a broadcast packet containing the cable identifier at a preset time interval with a fixed transmission power. Generating the directed edge sequence specifically includes: Each of the signal receivers receives the broadcast packet, extracts the cable identifier contained in the broadcast packet, measures the signal strength indicator value of the received signal, and packages the cable identifier, the signal strength indicator value, and the reception time into a reporting data packet; For each reporting time, based on the signal strength indication values ​​of the same cable identifier at at least three signal receivers, a preset logarithmic distance path loss model is used to convert each signal strength indication value into an estimated distance from the wireless beacon to each signal receiver. Based on the estimated distance and the known installation coordinates of each signal receiver, the weighted centroid positioning algorithm is used to calculate the estimated position coordinates of the wireless beacon at the reporting time. The estimated location coordinates are matched with the known coordinates of each key location point in the directed topology map to determine the key location point closest to the cable head at the reporting time. Determine the path segment containing the nearest critical location point as the path segment where the cable's head end is located at the reporting time; Arrange the path segments determined at each time point in chronological order, merge adjacent and repeated path segments, and obtain the directed edge sequence that has been traversed at the beginning of the cable. The extraction module is configured to extract time-series data of all preset monitoring points associated with a certain directed edge in the directed edge sequence according to the mapping relationship, so as to obtain a target time-series data set; The segmentation module is configured to adaptively segment the target time series data set into multiple action data segments corresponding to a single construction action, determine the construction action type corresponding to each action data segment, and arrange the determined construction action types in chronological order to obtain the actual construction action sequence. The accumulation module is configured to compare the actual construction action sequence with the preset standard action sequence template for laying procedures. If the matching degree of the comparison exceeds the preset procedure completion threshold, the path length value of a certain directed edge is accumulated into the laid length of the cable, and the laid length is divided by the total designed path length of the cable to obtain the laying progress of the cable.

8. An electronic device, characterized in that, include: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, it implements the method described in any one of claims 1 to 6.

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