An anti-electromagnetic interference signal reconstruction method of a double-system contact network inspection vehicle

Abstract

This application provides a method for reconstructing electromagnetic interference signals for a dual-mode overhead contact line inspection vehicle, relating to the field of data processing. In this method, detection data and vehicle operating status data are acquired to form inspection status data, and the influence relationships between the traction power supply system, detection equipment, and signal transmission lines are analyzed to establish an electromagnetic interference influence model. Based on the electromagnetic interference influence model, abnormal changes in the detection signals are identified, and electromagnetic interference events are determined by combining the power supply system and equipment status. Interference changes are extracted through signal correlation changes between multiple detection devices. The interference type and influence range are determined according to the interference patterns under different power supply systems. The affected abnormal detection signals are reconstructed, and the reconstructed electromagnetic interference signal is output. Implementing the technical solution provided in this application facilitates accurate identification of interference sources and effective detection information.

Description

Technical Field

[0001] This application relates to the technical field of data processing, specifically to a method for reconstructing electromagnetic interference signals for a dual-mode overhead contact line inspection vehicle. Background Technology

[0002] With the development of rail transit inspection technology, overhead contact line inspection vehicles are increasingly employing various types of inspection equipment to comprehensively monitor the operating status of the overhead contact line, including pantograph inspection devices, laser measurement devices, image acquisition equipment, inertial measurement units, and electrical inspection modules. These inspection devices are typically connected via onboard power supply systems, signal transmission lines, and the vehicle body structure to achieve synchronous data acquisition and comprehensive analysis.

[0003] However, dual-mode catenary inspection vehicles operate simultaneously under different power supply systems. During operation, their traction power supply systems generate electromagnetic disturbances such as high-frequency switching actions, arc discharges, changes in traction return current, and power supply system switching. These disturbances couple to the detection equipment via power supply lines, signal transmission lines, and the vehicle's grounding structure. Existing catenary inspection signal processing methods primarily focus on filtering and anomaly correction for individual detection devices, making it difficult to address the complex electromagnetic coupling interference generated by the traction power supply system, equipment connections, and signal transmission lines in dual-mode catenary inspection vehicles. When electromagnetic interference affects multiple detection devices, it can easily cause confusion between abnormal detection signals and actual changes in the catenary's condition, leading to an inability to accurately identify the source of interference and obtain effective detection information.

[0004] Therefore, there is an urgent need for a method for reconstructing electromagnetic interference signals for dual-mode overhead contact line inspection vehicles. Summary of the Invention

[0005] This application provides a method for reconstructing electromagnetic interference signals for a dual-mode overhead contact line inspection vehicle, which facilitates accurate identification of interference sources and effective detection information.

[0006] The first aspect of this application provides a method for reconstructing electromagnetic interference signals for a dual-mode overhead contact line inspection vehicle. The method includes: acquiring detection data and vehicle operating status data of the dual-mode overhead contact line inspection vehicle to form inspection status data; analyzing the influence relationship between the traction power supply system, detection equipment, and signal transmission lines based on the inspection status data to establish an electromagnetic interference influence model; identifying abnormal changes in detection signals based on the electromagnetic interference influence model, and determining electromagnetic interference events in conjunction with the power supply system and equipment status; analyzing signal changes of multiple detection devices through the electromagnetic interference events to extract interference changes corresponding to common changes in the detection devices; determining the interference type and interference influence range based on the interference changes and interference patterns under different power supply systems; reconstructing the abnormal detection signals according to the interference type and influence range, and outputting the electromagnetic interference signal reconstruction result.

[0007] A second aspect of this application provides an electromagnetic interference signal reconstruction device for a dual-mode overhead contact line inspection vehicle. The device includes an acquisition module and a processing module. The acquisition module acquires detection data and vehicle operating status data of the dual-mode overhead contact line inspection vehicle to form inspection status data. The processing module analyzes the influence relationship between the traction power supply system, detection equipment, and signal transmission lines based on the inspection status data to establish an electromagnetic interference influence model. The processing module is also used to identify abnormal changes in the detection signal based on the electromagnetic interference influence model and determine electromagnetic interference events in conjunction with the power supply system and equipment status. The processing module is further used to analyze signal changes of multiple detection devices through the electromagnetic interference events and extract interference changes corresponding to common changes in the detection devices. The processing module is also used to determine the interference type and interference influence range based on the interference changes and interference patterns under different power supply systems. The processing module is also used to reconstruct the abnormal detection signal according to the interference type and influence range and output the electromagnetic interference signal reconstruction result.

[0008] A third aspect of this application provides an electronic device comprising a processor and a memory; the memory stores a computer program, wherein the computer program, when executed by the processor, implements an electromagnetic interference signal reconstruction method for a dual-mode overhead contact line inspection vehicle as described above.

[0009] In a fourth aspect of this application, a non-transitory computer-readable storage medium is provided, the non-transitory computer-readable storage medium storing instructions that, when executed, perform an electromagnetic interference signal reconstruction method for a dual-mode overhead contact line inspection vehicle as described above.

[0010] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: By acquiring detection data and vehicle operating status data, inspection status data is generated. The influence relationships between the traction power supply system, detection equipment, and signal transmission lines are analyzed to establish an electromagnetic interference (EMI) impact model, enabling correlation analysis of EMI sources, propagation paths, and affected detection equipment. EMI events are identified by combining power supply system and equipment status. Interference changes corresponding to common changes are extracted through signal change relationships among multiple detection devices, distinguishing EMI from actual catenary status changes. The interference type and impact range are determined based on interference patterns under different power supply systems. Affected abnormal detection signals are reconstructed to match the actual EMI propagation process. These methods facilitate accurate identification of interference sources and effective detection information, improving the signal accuracy and stability of the inspection vehicle in complex electromagnetic environments and reducing the impact of EMI on catenary detection results. Attached Figure Description

[0011] Figure 1 A flowchart illustrating an electromagnetic interference signal reconstruction method for a dual-mode overhead contact line inspection vehicle provided in this application embodiment; Figure 2 A schematic diagram of an anti-electromagnetic interference signal reconstruction device for a dual-mode overhead contact line inspection vehicle provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0012] Explanation of reference numerals in the attached figures: 21. Acquisition module; 22. Processing module; 31. Processor; 32. Communication bus; 33. User interface; 34. Network interface; 35. Memory. Detailed Implementation

[0013] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0014] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0015] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0016] To address the aforementioned technical problems, this application provides a method for electromagnetic interference signal reconstruction in a dual-mode overhead contact line inspection vehicle, referring to... Figure 1 , Figure 1 This is a flowchart illustrating an electromagnetic interference signal reconstruction method for a dual-mode overhead contact line inspection vehicle, as provided in this application embodiment. The method is applied to a server and includes steps S110 to S160, as follows:

[0017] S110. Acquire the detection data and vehicle operation status data of the dual-mode overhead contact line inspection vehicle to form inspection status data.

[0018] Specifically, in this application, the server refers to a computing device used to perform data processing, analysis, calculation, and signal reconstruction tasks for the dual-mode catenary inspection vehicle. It can be an edge server deployed on the vehicle's onboard system or a remote server deployed at a ground control center. The server connects to the inspection equipment, vehicle control equipment, and data acquisition equipment on the inspection vehicle via a communication network to receive inspection data and vehicle operating status data, and to perform electromagnetic interference analysis and signal reconstruction processing. When acquiring inspection data and vehicle operating status data from the dual-mode catenary inspection vehicle, the server first establishes data communication connections with multiple inspection devices on the vehicle, receiving the inspection data collected by each device in real time. The inspection data includes catenary geometric parameter inspection data, pantograph-catenary status inspection data, electrical parameter inspection data, image inspection data, and inertial measurement data, etc. The data includes: contact wire geometric parameter detection data to reflect changes in contact wire height, offset, and geometric state; pantograph-catenary condition detection data to reflect the contact state between the pantograph and the contact wire; electrical parameter detection data to reflect power supply status, current changes, and voltage changes; image detection data to record the appearance of the contact wire; and inertial measurement data to reflect the attitude changes of the inspection vehicle during operation. The server receives detection data from different sources and stores it according to the type of detection equipment.

[0019] The server synchronously acquires vehicle operation status data corresponding to the dual-mode overhead contact line inspection vehicle, enabling the detection data to establish a correlation with the actual operating environment of the inspection vehicle. Vehicle operation status data includes power supply system status, vehicle speed status, vehicle location information, traction equipment operation status, pantograph operation status, and detection equipment working status. Specifically, the power supply system status indicates whether the inspection vehicle is currently powered by AC, DC, or switching power supply systems; the traction equipment operation status indicates the operating status of electrical equipment such as traction converters and auxiliary power supply equipment; the pantograph operation status indicates the pantograph's raising, lowering, current collection, and contact status; and the detection equipment working status indicates whether each detection device is currently in a normal data acquisition state. By acquiring this vehicle operation status data, the server provides a basis for subsequently determining whether changes in detection signals are affected by electromagnetic interference.

[0020] The server performs time correlation processing on the detection data and vehicle operating status data, ensuring a time-correlation relationship between data collected by different detection devices and changes in vehicle operating status. Because the sampling frequencies and data transmission cycles of different detection devices in the dual-mode overhead contact line inspection vehicle differ, the server performs time calibration based on the acquisition time information corresponding to each data point, matching data collected by different detection devices at the same operating moment to form synchronized detection data. Through time correlation processing, it can be determined whether an abnormal change in a detection signal occurs simultaneously with changes in power supply status, traction equipment operation, or pantograph status.

[0021] The server performs spatial correlation processing on the inspection vehicle's operating location and the vehicle's operating status data, establishing a mapping relationship between the inspection data and the corresponding line location. Spatial correlation processing refers to determining the contact wire section corresponding to the inspection data based on the vehicle's positioning information, enabling the server to determine whether a change in a certain detection signal occurs in a specific power supply area, line section, or equipment installation area. Through spatial correlation processing, the potential propagation range of electromagnetic interference can be further analyzed in conjunction with the line environment and equipment distribution.

[0022] The server integrates the detection data after completing time and spatial correlation with the vehicle operating status data to form inspection status data. This inspection status data comprehensively describes the data collected by the detection equipment, the vehicle's operating status, and changes in the power supply environment during the operation of the dual-system overhead contact line inspection vehicle. It includes not only information on changes in the detection signals themselves but also the vehicle operating conditions that cause these changes. By forming this inspection status data, a complete data foundation is provided for subsequent analysis of the influence relationships between the traction power supply system, detection equipment, and signal transmission lines, and for establishing an electromagnetic interference impact model.

[0023] S120. Analyze the influence relationship between the traction power supply system, detection equipment and signal transmission lines based on the inspection status data, and establish an electromagnetic interference influence model.

[0024] Specifically, the system acquires the operating status of the traction power supply system, detection equipment, and signal transmission lines based on inspection status data, and establishes equipment status association information. In practice, the server first extracts equipment operating information related to electromagnetic interference from the inspection status data. The operating status of the traction power supply system includes the power supply system status, traction converter equipment operating status, pantograph current collection status, and traction current change status; the operating status of the detection equipment includes the acquisition status, power supply status, and signal output status of each detection device; and the operating status of the signal transmission lines includes the signal transmission status, line connection status, and signal anomaly status. The server performs association matching based on the acquisition time, vehicle location, and equipment connection relationships corresponding to the above operating statuses to determine the correspondence between different equipment status changes, forming equipment status association information. This enables correlation analysis of status changes among the traction power supply system, detection equipment, and signal transmission lines.

[0025] Based on equipment status association information, the source of electromagnetic interference (EMI), affected detection equipment, and interference propagation path are determined. In practice, the server analyzes the state change relationships between the traction power supply system, detection equipment, and signal transmission lines to identify the equipment source causing abnormal signal changes. Specifically, the traction converter equipment causing abnormal signal changes, the pantograph current collection process, and the power supply mode switching process are identified as EMI sources; the detection equipment exhibiting abnormal signal changes is identified as affected detection equipment; and the power supply lines, signal transmission lines, and vehicle grounding structures traversed by the EMI source to the affected detection equipment are identified as interference propagation paths. By determining the EMI source, affected detection equipment, and interference propagation path, a correspondence is established between the EMI generation process, propagation process, and impact outcome.

[0026] Among them, electromagnetic interference sources refer to equipment or operating processes that generate electromagnetic disturbances during the operation of dual-mode catenary inspection vehicles, such as the high-frequency switching action of traction converter equipment, arc discharge between pantograph and catenary, and changes in electrical state during power supply mode switching; affected detection equipment refers to detection equipment that is affected by electromagnetic interference and produces abnormal changes in detection signals, such as catenary geometric detection equipment, pantograph-catenary condition detection equipment, electrical detection equipment, and image acquisition equipment; interference propagation path refers to the path of electromagnetic interference from the location of generation to the detection equipment, including conduction paths through power lines, coupling paths through signal lines, and structural propagation paths through the vehicle body structure and grounding system.

[0027] Based on the electromagnetic interference (EMI) source, affected detection equipment, and interference propagation path, a device impact graph is constructed, and an EMI impact model is generated. In practice, the server converts the EMI source, affected detection equipment, and interference propagation path into associated objects in the device impact graph. Specifically, the EMI source is treated as an interference node, the affected detection equipment as a detection node, and the interference propagation path as the connection relationship between nodes. These connections represent the propagation process of EMI between different devices. For example, EMI generated by traction converter equipment affects electrical detection equipment through power supply lines and catenary detection equipment through signal transmission lines; corresponding connections are then established in the device impact graph.

[0028] The server further categorizes the equipment influence diagrams generated under different power supply systems, recording the electromagnetic interference propagation relationships under AC power supply, DC power supply, and power supply system switching conditions. Since the operating modes, current variation patterns, and electromagnetic interference characteristics of traction equipment differ under different power supply systems, classifying the equipment influence diagrams under different power supply systems allows the generated electromagnetic interference influence model to adapt to different operating environments.

[0029] The server generates an electromagnetic interference (EMI) impact model based on the categorized equipment influence relationship diagram. This model enables the server to determine the corresponding EMI source, affected detection equipment, and interference propagation path based on the current inspection status data. When subsequent detection signals exhibit abnormal changes, the server matches the corresponding equipment relationships and propagation paths using the EMI impact model to determine whether the abnormal change is caused by EMI. This provides a basis for subsequently identifying EMI events, extracting interference changes, and performing signal reconstruction. By establishing the EMI impact model, the complex electromagnetic coupling relationships of dual-system overhead contact line inspection vehicles can be described, avoiding the need to determine the source of anomalies based solely on a single detection signal and improving the accuracy of the anti-EMI signal reconstruction process.

[0030] In one possible implementation, corresponding interference nodes are determined based on the source of electromagnetic interference, and corresponding detection nodes are determined based on the affected detection equipment. Specifically, the server first extracts the identified sources of electromagnetic interference and affected detection equipment from the equipment status association information. The source of electromagnetic interference represents the equipment or operating process that generates electromagnetic disturbances, such as high-frequency switching actions of traction converter equipment, arc discharge between the pantograph and the contact network, and changes in electrical state during power supply system switching. Affected detection equipment represents equipment affected by electromagnetic interference and exhibiting changes in detection signals, such as contact network geometric detection equipment, pantograph-catenary status detection equipment, electrical detection equipment, and image acquisition equipment. The server marks the sources of electromagnetic interference as interference nodes and the affected detection equipment as detection nodes, enabling different devices to be associated and described in node form during subsequent analysis.

[0031] The connection relationship between interfering nodes and detection nodes is determined based on the interference propagation path, and a device impact diagram is constructed. In practice, the server obtains the propagation process of electromagnetic interference from its source to the affected detection equipment based on equipment status association information. The interference propagation path represents the transmission method of electromagnetic interference within the dual-mode catenary inspection vehicle, including conduction paths through power supply lines, coupling paths through signal transmission lines, and structural propagation paths through the vehicle structure and grounding system. The server determines the connection direction between interfering nodes and detection nodes based on the interference propagation path and establishes corresponding connection relationships. For example, when electromagnetic interference generated by the traction converter affects electrical detection equipment through the power supply line, a power supply line connection is established between the corresponding interfering node and the detection node; when electromagnetic interference affects catenary detection equipment through the signal transmission line, a signal transmission connection is established between the corresponding interfering node and the detection node. Through this method, the electromagnetic interference source, affected detection equipment, and interference propagation process are converted into a device impact diagram.

[0032] The equipment influence relationship diagram is used to describe the electromagnetic interference relationships between the internal equipment of the dual-mode overhead contact line inspection vehicle. The nodes in the diagram include interference nodes and detection nodes. Interference nodes indicate the location of electromagnetic interference, and detection nodes indicate the affected detection equipment. Connections represent the propagation paths of electromagnetic interference between different devices. This diagram visually illustrates the propagation process of different electromagnetic interference sources affecting different detection devices, providing a basis for identifying abnormal changes in detection signals.

[0033] Based on the equipment influence relationship diagrams under different power supply systems, corresponding electromagnetic interference propagation relationships are established. In practice, the server categorizes the constructed equipment influence relationship diagrams according to the power supply system status in the inspection status data. The power supply system status includes AC power supply status, DC power supply status, and power supply system switching status. Because the operating mode, equipment working status, and electromagnetic interference characteristics of the traction power supply system differ under different power supply systems, the server extracts the corresponding interference nodes, detection nodes, and connection relationships under different power supply system statuses and establishes corresponding electromagnetic interference propagation relationships. For example, under AC power supply status, the server records the electromagnetic interference propagation relationship generated by the operation of the traction converter equipment; under DC power supply status, the server records the electromagnetic interference propagation relationship generated by changes in traction return current; and under power supply system switching status, the server records the transient electromagnetic interference propagation relationship generated by equipment switching actions.

[0034] An electromagnetic interference (EMI) impact model is generated based on EMI propagation relationships. In practice, the server integrates EMI propagation relationships established under different power supply conditions to form an EMI impact model that describes the EMI propagation process under different operating conditions. This model is used to determine the corresponding EMI source, affected detection equipment, and interference propagation path based on current inspection status data. When abnormal changes occur in the detection signal, the server matches the current power supply status and equipment operating status using the EMI impact model to determine whether the abnormal change conforms to existing EMI propagation relationships, thereby judging whether the abnormal detection signal is caused by EMI.

[0035] The electromagnetic interference impact model generated in the above manner provides a structured description of the electromagnetic coupling relationship between the traction power supply system, detection equipment, and signal transmission lines inside the dual-mode catenary inspection vehicle. This transforms electromagnetic interference from signal anomalies that cannot be directly analyzed into a correlation with sources, paths, and affected objects, providing a foundation for subsequent electromagnetic interference event identification, interference change extraction, and anomaly detection signal reconstruction.

[0036] S130. Identify abnormal changes in the detection signal based on the electromagnetic interference influence model, and determine the electromagnetic interference event by combining the power supply system and equipment status.

[0037] Specifically, based on the electromagnetic interference (EMI) impact model, the affected detection devices and interference propagation paths corresponding to the detection signals are obtained. The changing states of the detection signals are then matched with the affected detection devices. In practice, the server first invokes the EMI impact model to obtain the set of detection devices potentially affected by EMI and their corresponding interference propagation paths based on the current inspection status data. Affected detection devices refer to those whose detection signals may change abnormally during EMI propagation, such as catenary geometry detection devices, pantograph-catenary condition detection devices, electrical detection devices, and image acquisition devices. The interference propagation path refers to the process by which EMI is transmitted from its source to the affected detection devices, including propagation paths along power supply lines, signal transmission lines, and vehicle structures. The server further obtains the changing states of the detection signals collected by each detection device and matches these changes with the affected detection devices to determine whether the abnormally changing detection devices are within the influence range defined by the EMI impact model.

[0038] Based on the matching results, the time, amplitude, and location of abnormal changes in the detection signal are obtained. Combined with the power supply system status, vehicle operating status, and equipment operating status, candidate electromagnetic interference changes are identified. Specifically, the server extracts the change features corresponding to the abnormal detection signal based on the matching results between the detection signal and the affected detection equipment. The abnormal change time indicates the time node when the detection signal undergoes an abnormal change; the change amplitude indicates the degree of change of the detection signal relative to its normal state; and the change location indicates the location of the line or detection equipment corresponding to the abnormal detection signal. The server performs correlation analysis with the power supply system status, vehicle operating status, and equipment operating status in the inspection status data. For example, it determines whether the abnormal change occurs during a power supply system switching process, traction equipment startup process, pantograph current collection change process, or detection equipment operating status change process. When there is a time correspondence between the abnormal change in the detection signal and the aforementioned operating status changes, and the detection equipment corresponding to the abnormal detection signal is within the affected range determined by the electromagnetic interference influence model, the abnormal change is identified as a candidate electromagnetic interference change.

[0039] Among them, candidate electromagnetic interference changes refer to abnormal changes in detection signals that are initially judged to be caused by electromagnetic interference, but whose source has not yet been confirmed. Since changes in the condition of the contact network, equipment malfunctions, and electromagnetic coupling interference can all cause changes in the detection signals during the operation of the dual-mode contact network inspection vehicle, it is necessary to further consider the electromagnetic interference propagation relationship to avoid misjudging actual changes in the condition of the contact network as electromagnetic interference.

[0040] By associating candidate electromagnetic interference (EMI) changes with the EMI sources and propagation paths in the EMI impact model, EMI changes that conform to the EMI propagation relationship are identified as EMI events. Specifically, the server matches the detection equipment, change location, and abnormal change time corresponding to the candidate EMI change with the EMI sources and propagation paths in the EMI impact model. The EMI source represents the equipment or operating process that generates the electromagnetic disturbance, such as high-frequency switching of traction converter equipment, pantograph arcing, and power supply mode switching. The propagation path represents the transmission relationship between the EMI source and the detection equipment. The server determines whether the candidate EMI change can be transmitted from the EMI source to the corresponding affected detection equipment along the propagation path.

[0041] When the detection device, anomalous change time, and change location corresponding to a candidate electromagnetic interference change all match the electromagnetic interference source and interference propagation path in the electromagnetic interference impact model, the server identifies the candidate electromagnetic interference change as an electromagnetic interference event. An electromagnetic interference event represents a confirmed anomalous change in the detection signal caused by electromagnetic interference, and includes information on the electromagnetic interference source, affected detection device, interference propagation path, and anomalous detection signal change. Identifying electromagnetic interference events provides a basis for subsequent analysis of interference changes corresponding to changes in multiple detection devices, determining the interference type, and reconstructing anomalous detection signals. This processing method avoids the problem of traditional methods that only determine the source of anomalies based on changes in detection signals, enabling effective differentiation between changes in the actual contact network state and changes in electromagnetic coupling interference.

[0042] S140. Analyze the signal changes of multiple detection devices through electromagnetic interference events, and extract the interference changes corresponding to the common changes of the detection devices.

[0043] Specifically, the affected detection devices are identified based on electromagnetic interference (EMI) events, and their corresponding detection signals are acquired. In practice, the server first retrieves the set of affected detection devices from the EMI impact model based on the identified EMI events. This set refers to multiple detection devices within the current EMI event's influence range that may exhibit abnormal signal changes, such as overhead contact line geometry detection devices, pantograph-catenary condition detection devices, electrical detection devices, and image acquisition devices. Based on this set, the server extracts the detection signals acquired by the corresponding devices from the inspection status data and stores them in association according to device number, acquisition time, and line location, forming a multi-device detection signal set. By acquiring the detection signals corresponding to multiple affected devices, the common impacts of EMI can be identified subsequently based on the shared changes among these devices.

[0044] The system synchronizes the detection signals from multiple detection devices in time, analyzing the time, amplitude, and trend of change for each device. Specifically, the server calibrates the detection signals from different devices based on the timestamps corresponding to the acquisition of the signals. Because different detection devices have different data sampling frequencies, data transmission cycles, and processing delays, the server uses time synchronization to ensure that the detection signals from multiple devices remain consistent within the same time window. A time window refers to a continuous time range used to analyze the impact of the same electromagnetic interference event.

[0045] After time synchronization is complete, the server extracts the signal change characteristics of each detection device within the time window. The change time indicates the location of any abnormal signal change; the change amplitude indicates the degree of change relative to the normal state; and the change trend indicates the direction of continuous change in the signal, such as continuous increase, continuous decrease, or periodic fluctuation. By analyzing the change characteristics of multiple detection devices, the server provides data to determine whether multiple detection devices are affected by the same electromagnetic interference.

[0046] Based on the correlation between changes in multiple detection devices, synchronous changes in detection signals with consistent trends are identified as interference changes. In practice, the server performs correlation analysis on the change time, amplitude, and trend of multiple detection devices to determine whether the changes in the detection signals of different devices are synchronous. When multiple detection devices exhibit abnormal changes within the same time range, and the change trends are consistent, it indicates that the change may be caused by the same electromagnetic interference source, and the server identifies the corresponding detection signal change as a candidate interference change.

[0047] The change correlation is used to describe the degree of consistency of signal changes among multiple detection devices. The server determines whether there is a common response relationship between the detection devices by comparing whether the change time of different detection devices overlaps, whether the change direction is consistent, and whether the change process is synchronized. For example, when the traction converter generates high-frequency switching interference, multiple detection devices may show signal fluctuations at the same time. If the abnormal change time of these detection devices is consistent and the change trend is the same, then this part of the change is considered to originate from the same electromagnetic interference and is identified as interference change.

[0048] By matching interference changes with the interference propagation paths in the electromagnetic interference (EMI) impact model, interference changes that conform to the propagation paths are separated from valid detection signals. Specifically, the server matches the detection device, change location, and change time corresponding to the interference change with the interference propagation path in the EMI impact model. The interference propagation path represents the process of electromagnetic interference propagating from the source to the affected detection device, including propagation paths along power supply lines, signal transmission lines, and vehicle structures.

[0049] The server determines whether the detection device corresponding to the interference change is located within the affected area corresponding to the interference propagation path, and whether the time of the interference change corresponds to the electromagnetic interference propagation process. When the detection device, the time of change, and the location of the change all conform to the interference propagation path, the interference change is identified as a signal change caused by electromagnetic interference and separated from the detection signal.

[0050] After separating interference changes, the server retains the portion of the signal unaffected by the interference changes as the valid detection signal. The valid detection signal refers to the portion of the detection signal that reflects the actual operating status of the overhead contact line, including real detection information such as changes in overhead contact line geometry, changes in pantograph-catenary contact state, and changes in equipment operating status. By separating interference changes that conform to the interference propagation path from the valid detection signal, the subsequent signal reconstruction process can address anomalies caused by electromagnetic interference, avoiding impact on the actual overhead contact line status information.

[0051] Through the above process, the analysis scope is determined by electromagnetic interference events, interference changes are extracted based on the common change relationships between multiple detection devices, and interference change identification and effective detection signal separation are completed by combining the interference propagation path in the electromagnetic interference influence model. This makes electromagnetic interference no longer regarded as random noise in a single detection signal, but as a correlated change with source, propagation path and multi-device response characteristics, thus improving the signal processing accuracy of the dual-mode catenary inspection vehicle in the complex electromagnetic environment.

[0052] S150. Based on interference changes and interference patterns under different power supply systems, determine the interference type and interference impact range.

[0053] Specifically, the system obtains the corresponding power supply status based on interference changes and matches the interference changes with the interference patterns under different power supply systems to determine the target interference type. In practice, the server first obtains the power supply status corresponding to the time the interference change occurs from the inspection status data. The power supply status represents the current operating environment of the dual-system overhead contact line inspection vehicle, including AC power supply status, DC power supply status, and power supply system switching status. The server then calls the corresponding set of interference patterns based on the power supply status. This set of interference patterns describes the changing characteristics of electromagnetic interference under different power supply systems, including the time of interference change, the magnitude of the change, the duration of the change, and the range of affected detection equipment. The server matches the changing characteristics corresponding to the interference change with the standard interference characteristics in the set of interference patterns to determine the similarity between the interference change and the electromagnetic interference patterns under different power supply systems.

[0054] Interference change refers to signal changes occurring simultaneously from multiple detection devices and conforming to electromagnetic interference propagation relationships. Target interference type refers to the specific electromagnetic interference category determined based on the characteristics of the interference change, such as traction converter switching interference, pantograph arcing interference, power supply mode switching interference, and return current change interference. To improve the accuracy of distinguishing different interference types, the server establishes interference matching results based on the change time, change trend, and range of changing devices corresponding to the interference change. The matching expression is as follows:

[0055] in, This indicates the degree of matching between the changes in interference and the pattern of interference from the target, and its value ranges from 0 to 1. Indicates the first The characteristics of the disturbance change include the change time, change magnitude, change duration, and change trend. Indicates the first The standard interference characteristics corresponding to each power supply system are obtained by statistical analysis of electromagnetic interference events under the same power supply system in historical inspection status data. This indicates the number of interference variation features participating in the matching process, determined based on the actual types of interference features collected. When the matching degree reaches the preset requirements, the server will determine the standard interference type under the corresponding power supply system as the target interference type.

[0056] Based on the interference propagation path corresponding to the target interference type, the detection devices affected by the interference change are identified, and the interference impact range is determined. Specifically, the server retrieves the corresponding interference propagation path from the electromagnetic interference impact model based on the identified target interference type. The interference propagation path represents the process of the target interference type being transmitted from the electromagnetic interference source to the detection device, including power line propagation paths, signal transmission line propagation paths, and structural conduction paths. The server tracks the interference propagation path, identifies the detection devices located along it, and determines these devices as those affected by the interference change. The server further determines the interference impact range based on the positional relationships, device connection relationships, and signal transmission relationships of the affected detection devices. The interference impact range refers to the spatial and device range within which the target interference type can affect the detection signal, including the set of affected detection devices and the corresponding line area. By analyzing the length, direction, and number of connected devices of the interference propagation path corresponding to the target interference type, the server determines the interference impact range, ensuring that the subsequent signal reconstruction process is only performed on abnormal detection signals affected by electromagnetic interference.

[0057] An interference impact record is generated based on the target interference type and its affected range for reconstructing abnormal detection signals. Specifically, the server associates and stores the identified target interference type, its affected range, and corresponding interference changes to form the interference impact record. This record documents the complete impact information of an electromagnetic interference event, including the source of the interference, the target interference type, the affected detection equipment, the interference propagation path, and the range of the abnormal detection signal. The server then uses the interference impact record to determine the abnormal detection signals requiring reconstruction and invokes the signal reconstruction method corresponding to the target interference type.

[0058] For example, for interference types affecting multiple detection devices, common interference components are removed based on the interference change extraction results; for interference types affecting only a few detection devices, compensation and correction are performed based on the valid detection signals of the unaffected detection devices; for transient interference caused by power supply system switching, abnormal detection signals are recovered based on the detection status before and after the power supply system switching. Through the above process, the server classifies interference changes using the power supply system status, determines the target interference type based on the interference patterns under different power supply systems, and determines the interference impact range based on the interference propagation path corresponding to the target interference type. This ultimately forms an interference impact record to guide the reconstruction of abnormal detection signals, enabling the signal reconstruction process to match the actual electromagnetic interference source and propagation range, thus improving the accuracy of detection signal recovery in the complex electromagnetic environment of dual-system contact network inspection vehicles.

[0059] S160. Reconstruct the abnormal detection signal according to the interference type and the range of influence, and output the reconstruction result of the anti-electromagnetic interference signal.

[0060] Specifically, based on the interference type and scope of interference in the interference impact record, the affected detection devices and target detection signals are determined, and valid detection signals corresponding to unaffected detection devices are acquired. In practice, the server first reads the target interference type, the set of affected detection devices, and the scope of interference in the interference impact record. The interference impact record describes the impact information of an electromagnetic interference event, including the type of device generating the interference, the interference propagation range, and the affected detection devices. The server determines the detection devices within the electromagnetic interference propagation area based on the interference impact range and identifies these devices as affected detection devices. The server further extracts the detection signals collected by the affected detection devices from the inspection status data and identifies the detection signals affected by electromagnetic interference as target detection signals. Simultaneously, the server filters detection devices not in the interference propagation path based on the interference impact record and acquires valid detection signals corresponding to unaffected detection devices. Valid detection signals refer to detection signals that are not affected by the current electromagnetic interference event and can reflect the true operating status of the contact network. Acquiring valid detection signals provides a basis for recovering abnormal parts of the target detection signals.

[0061] The server determines the corresponding signal reconstruction method based on the interference type and corrects the interference changes in the target detection signal based on the effective detection signal. Specifically, the server calls the corresponding signal reconstruction method according to the target interference type. The signal reconstruction method refers to the abnormal signal recovery method used for different types of electromagnetic interference, including interference change removal, signal trend compensation, and abnormal segment recovery. When the interference type is coupled interference affecting multiple detection devices, the server removes the common changes of multiple detection devices from the target detection signal based on the extracted interference changes, retaining the effective changes reflecting the contact network status. When the interference type is interference affecting only a few detection devices, the server compensates for the abnormal changes in the target detection signal based on the change trend of the effective detection signal corresponding to the unaffected detection devices. When the interference type is transient interference caused by power supply system switching, the server continuously restores the target detection signal based on the change state of the effective detection signal before and after the power supply system switching. The server determines the interference correction result based on the change relationship between the effective detection signal and the target detection signal; the correction process can be described by the signal consistency relationship.

[0062] in, This represents the reconstructed target detection signal; This indicates the target detection signal affected by electromagnetic interference. This indicates the interference changes identified from the target detection signal, which are determined based on the common changes from multiple detection devices and the propagation path of electromagnetic interference. This indicates a compensation change generated based on the effective detection signal, which is determined according to the change trend of the effective detection signal corresponding to the unaffected detection equipment. This indicates the acquisition time corresponding to the detected signal. Among these, interference variation... The acquisition method is as follows: The server determines the set of affected detection devices based on the interference impact record, extracts the synchronous change portion from the detection signals corresponding to multiple affected detection devices, and filters the change portion that conforms to the propagation relationship based on the electromagnetic interference propagation path. The filtered change portion is determined as the interference change. Compensation change. The acquisition method is as follows: the server acquires the valid detection signal corresponding to the unaffected detection device, analyzes the change trend of the valid detection signal at the current inspection position and operating status, and generates the recovery change corresponding to the target detection signal based on the change trend.

[0063] The server performs a consistency check between the corrected target detection signal and the inspection status data. If the consistency requirements are met, the reconstructed anti-electromagnetic interference signal is output. Specifically, the server re-associates the reconstructed target detection signal with the inspection status data and performs a consistency analysis based on the power supply system status, vehicle operating status, and valid detection signals from other detection devices. The consistency check determines whether the reconstructed target detection signal conforms to the normal variation patterns under the current inspection environment. The server first determines whether the reconstructed target detection signal maintains a consistent trend with the valid detection signals from unaffected detection devices, and then determines whether the reconstructed target detection signal conforms to the detection patterns corresponding to the current power supply system status, vehicle operating speed, and overhead contact line operating status. When the reconstructed target detection signal no longer exhibits abnormal changes consistent with the electromagnetic interference propagation path and maintains consistency with the inspection status data, the reconstructed target detection signal is identified as the anti-electromagnetic interference signal reconstruction result. To evaluate the consistency between the reconstruction result and the inspection status, the server can establish a consistency evaluation relationship:

[0064] in, This indicates the consistency result of signal reconstruction. The closer the value is to the preset range, the more the reconstruction result matches the inspection status. Indicates the first The actual detection status characteristics corresponding to each inspection status are obtained from the unaffected detection equipment and vehicle operation status information in the inspection status data. Indicates the first The reconstructed detection state features corresponding to each inspection state are extracted from the reconstructed target detection signal. This indicates the number of inspection status features participating in the consistency verification, determined based on the number of status features included in the current detection task. When the consistency evaluation result meets the preset requirements, the server outputs the electromagnetic interference-resistant signal reconstruction result; when the consistency evaluation result does not meet the requirements, the server readjusts the corresponding signal reconstruction method according to the interference type and executes the abnormal detection signal correction process again. Through the above processing method, the server determines the target detection signal that needs to be corrected based on the interference type and the interference impact range, and uses the effective detection signal corresponding to the unaffected detection equipment to recover the detection signal contaminated by electromagnetic interference, making the reconstruction process match the actual electromagnetic interference propagation process, and improving the accuracy of detection data of the dual-system contact network inspection vehicle in complex electromagnetic environments.

[0065] This application also provides an electromagnetic interference signal reconstruction device for a dual-mode overhead contact line inspection vehicle, referring to... Figure 2 , Figure 2 This is a schematic diagram of a module for an anti-electromagnetic interference signal reconstruction device for a dual-mode catenary inspection vehicle, provided in an embodiment of this application. The device is a server, which includes an acquisition module 21 and a processing module 22. The acquisition module 21 is used to acquire detection data and vehicle operating status data of the dual-mode catenary inspection vehicle to form inspection status data. The processing module 22 is used to analyze the influence relationship between the traction power supply system, detection equipment, and signal transmission lines based on the inspection status data, and establish an electromagnetic interference influence model. The processing module 22 is also used to identify abnormal changes in detection signals based on the electromagnetic interference influence model, and determine electromagnetic interference events in combination with the power supply system and equipment status. The processing module 22 is also used to analyze the signal changes of multiple detection devices through electromagnetic interference events and extract the interference changes corresponding to the common changes of the detection devices. The processing module 22 is also used to determine the interference type and interference influence range based on the interference changes and the interference patterns under different power supply systems. The processing module 22 is also used to reconstruct the abnormal detection signals according to the interference type and influence range, and output the anti-electromagnetic interference signal reconstruction results.

[0066] It should be noted that the above embodiments of the apparatus are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0067] This application also provides an electronic device, with reference to... Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: at least one processor 31, at least one network interface 34, a user interface 33, a memory 35, and at least one communication bus 32.

[0068] The communication bus 32 is used to enable communication between these components.

[0069] The user interface 33 may include a display screen and a camera. Optionally, the user interface 33 may also include a standard wired interface and a wireless interface.

[0070] The network interface 34 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0071] The processor 31 may include one or more processing cores. The processor 31 connects to various parts of the server via various interfaces and lines, executing instructions, programs, code sets, or instruction sets stored in the memory 35, and calling data stored in the memory 35 to perform various server functions and process data. Optionally, the processor 31 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 31 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content to be displayed on the screen; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 31 and may be implemented as a separate chip.

[0072] The memory 35 may include random access memory (RAM) or read-only memory. Optionally, the memory 35 may include a non-transitory computer-readable storage medium. The memory 35 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 35 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 35 may also be at least one storage device located remotely from the aforementioned processor 31. Figure 3 As shown, the memory 35, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for an electromagnetic interference signal reconstruction method for a dual-mode overhead contact line inspection vehicle.

[0073] exist Figure 3 In the electronic device shown, the user interface 33 is mainly used to provide an input interface for the user and to obtain the user input data; while the processor 31 can be used to call the application program stored in the memory 35 for an anti-electromagnetic interference signal reconstruction method for a dual-mode contact network inspection vehicle. When executed by one or more processors, the electronic device executes one or more methods as described in the above embodiments.

[0074] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0075] This application also provides a non-transitory computer-readable storage medium storing instructions. When executed by one or more processors, these instructions cause an electronic device to perform one or more of the methods described in the above embodiments.

[0076] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0077] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings or direct couplings or communication connections may be through some service interfaces; indirect couplings or communication connections between apparatuses or units may be electrical or other forms.

[0078] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0079] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0080] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0081] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of other embodiments of this disclosure upon considering the specification and the disclosure of practical truth. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for reconstructing electromagnetic interference signals for a dual-mode overhead contact line inspection vehicle, characterized in that, The method includes: Acquire detection data and vehicle operation status data of dual-mode overhead contact line inspection vehicles to form inspection status data; Based on the inspection status data, analyze the influence relationship between the traction power supply system, detection equipment and signal transmission lines, and establish an electromagnetic interference influence model. Based on the electromagnetic interference impact model, abnormal changes in the detection signal are identified, and electromagnetic interference events are determined by combining the power supply system and equipment status. By analyzing the signal changes of multiple detection devices through the electromagnetic interference events, the interference changes corresponding to the common changes of the detection devices are extracted. Based on the aforementioned interference changes and interference patterns under different power supply systems, the interference type and interference impact range are determined. The abnormal detection signal is reconstructed based on the interference type and the range of influence, and the anti-electromagnetic interference signal reconstruction result is output.

2. The electromagnetic interference signal reconstruction method for a dual-mode overhead contact line inspection vehicle according to claim 1, characterized in that, The step of analyzing the influence relationship between the traction power supply system, detection equipment, and signal transmission lines based on the inspection status data, and establishing an electromagnetic interference influence model, specifically includes: Based on the inspection status data, the operating status of the traction power supply system, detection equipment and signal transmission lines is obtained, and equipment status association information is established. The source of electromagnetic interference, the affected detection equipment, and the interference propagation path are determined based on the device status association information. Based on the electromagnetic interference source, the affected detection equipment, and the interference propagation path, a device influence relationship diagram is constructed, and the electromagnetic interference influence model is generated.

3. The electromagnetic interference signal reconstruction method for a dual-mode overhead contact line inspection vehicle according to claim 1, characterized in that, The process of identifying abnormal changes in the detection signal based on the electromagnetic interference impact model, and determining electromagnetic interference events in conjunction with the power supply system and equipment status, specifically includes: Based on the electromagnetic interference influence model, the affected detection devices and interference propagation paths corresponding to the detection signals are obtained, and the change state of the detection signals is matched with the affected detection devices; Based on the matching results, the abnormal change time, change amplitude and change location of the detected signal are obtained, and candidate electromagnetic interference changes are determined in combination with the power supply system status, vehicle operation status and equipment operation status. By associating the candidate electromagnetic interference changes with the electromagnetic interference sources and propagation paths in the electromagnetic interference impact model, the candidate electromagnetic interference changes that conform to the electromagnetic interference propagation relationship are identified as the electromagnetic interference events.

4. The electromagnetic interference signal reconstruction method for a dual-mode overhead contact line inspection vehicle according to claim 1, characterized in that, The step of analyzing the signal changes of multiple detection devices through the electromagnetic interference event and extracting the interference changes corresponding to the common changes of the detection devices specifically includes: The affected detection equipment is identified based on the electromagnetic interference event, and the detection signal corresponding to the affected detection equipment is obtained; The detection signals corresponding to multiple detection devices are synchronized in time, and the change time, change amplitude and change trend of each detection device are analyzed. Based on the correlation between the changes of the multiple detection devices, the synchronous changes of detection signals with consistent trends are identified as interference changes; By matching the interference changes with the interference propagation path in the electromagnetic interference influence model, interference changes that conform to the interference propagation path are separated from the effective detection signal.

5. The electromagnetic interference signal reconstruction method for a dual-mode overhead contact line inspection vehicle according to claim 1, characterized in that, The determination of interference type and interference impact range based on the interference changes and interference patterns under different power supply systems specifically includes: The corresponding power supply system status is obtained based on the interference changes, and the interference changes are matched with the interference patterns under different power supply systems to determine the target interference type. Based on the interference propagation path corresponding to the target interference type, the detection devices affected by the interference change are obtained, and the interference impact range is determined; An interference impact record is generated based on the target interference type and the interference impact range, which is used for reconstructing the anomaly detection signal.

6. The electromagnetic interference signal reconstruction method for a dual-mode overhead contact line inspection vehicle according to claim 5, characterized in that, The process of reconstructing the abnormal detection signal based on the interference type and its range of influence, and outputting the electromagnetic interference signal reconstruction result, specifically includes: Based on the interference type and interference range in the interference impact record, the affected detection devices and target detection signals are determined, and the valid detection signals corresponding to the unaffected detection devices are obtained. The corresponding signal reconstruction method is determined according to the type of interference, and the interference changes in the target detection signal are corrected based on the effective detection signal; The consistency of the corrected target detection signal and the inspection status data is verified, and the anti-electromagnetic interference signal reconstruction result is output when the consistency requirements are met.

7. The electromagnetic interference signal reconstruction method for a dual-mode overhead contact line inspection vehicle according to claim 2, characterized in that, The process of constructing a device impact relationship diagram based on the electromagnetic interference source, the affected detection equipment, and the interference propagation path, and generating the electromagnetic interference impact model, specifically includes: The corresponding interference node is determined based on the source of the electromagnetic interference, and the corresponding detection node is determined based on the affected detection equipment; The connection relationship between the interfering node and the detection node is determined based on the interference propagation path, and a device influence relationship diagram is constructed. Based on the equipment influence relationship diagram under different power supply systems, the corresponding electromagnetic interference propagation relationships are established by classifying them. The electromagnetic interference impact model is generated based on the electromagnetic interference propagation relationship.

8. An electromagnetic interference signal reconstruction device for a dual-mode overhead contact line inspection vehicle, characterized in that, The device is used to perform the electromagnetic interference signal reconstruction method for a dual-mode overhead contact line inspection vehicle as described in any one of claims 1 to 7. The device includes an acquisition module and a processing module, wherein... The acquisition module is used to acquire the detection data and vehicle operation status data of the dual-mode overhead contact line inspection vehicle to form inspection status data. The processing module is used to analyze the influence relationship between the traction power supply system, detection equipment and signal transmission lines based on the inspection status data, and to establish an electromagnetic interference influence model. The processing module is also used to identify abnormal changes in the detection signal based on the electromagnetic interference influence model, and to determine electromagnetic interference events in combination with the power supply system and equipment status. The processing module is also used to analyze the signal changes of multiple detection devices through the electromagnetic interference event and extract the interference changes corresponding to the common changes of the detection devices; The processing module is also used to determine the interference type and interference range based on the interference changes and the interference patterns under different power supply systems. The processing module is also used to reconstruct the abnormal detection signal according to the interference type and the range of influence, and output the anti-electromagnetic interference signal reconstruction result.

9. An electronic device, characterized in that, The electronic device includes a processor and a memory; the memory stores a computer program, wherein the computer program, when executed by the processor, implements an anti-electromagnetic interference signal reconstruction method for a dual-mode overhead contact line inspection vehicle as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores instructions that, when executed, perform an anti-electromagnetic interference signal reconstruction method for a dual-mode overhead contact line inspection vehicle as described in any one of claims 1 to 7.

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