A method, system, and medium for drone wiring harness layout

Abstract

The application discloses a kind of unmanned aerial vehicle wire harness layout method, it is related to unmanned aerial vehicle wire harness layout technical field.The unmanned aerial vehicle wire harness layout method includes the following steps: electromagnetic coupling interference monitoring;Unmanned aerial vehicle wire harness intersection condition monitoring;Signal fluctuation condition monitoring.The application is evaluated by carrying out unmanned aerial vehicle wire harness electromagnetic coupling interference, if unmanned aerial vehicle wire harness electromagnetic coupling interference evaluation is qualified, then carry out unmanned aerial vehicle signal fluctuation condition analysis, whether need to send signal fluctuation abnormal alarm based on the unmanned aerial vehicle signal fluctuation condition analysis result of acquisition judges, otherwise, then carry out unmanned aerial vehicle wire harness intersection condition statistics quantification, whether need to take wire harness layout adjustment based on the unmanned aerial vehicle wire harness intersection condition statistics quantification result of acquisition judges, reaches the effect of improving unmanned aerial vehicle monitoring network data link stability, solves the problem of low stability of existing technology in unmanned aerial vehicle monitoring network data transmission.

Description

A method, system and medium for laying out wiring harnesses for unmanned aerial vehicles (UAVs). Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) wiring harness layout technology, and in particular to a UAV wiring harness layout method, system and medium. Background Technology

[0002] The rationality of the drone wiring harness layout directly affects flight safety and operational reliability. A messy wiring harness layout or insufficient interference resistance can easily lead to major malfunctions (such as signal interruption, short circuits, and fires). Furthermore, an unreasonable layout increases redundant weight and affects endurance. Therefore, a systematic process is needed for wiring harness layout: First, based on existing 3D modeling technologies (such as CAD, CATIA, and other engineering software), a precise digital model of the drone's airframe structure and electronic components is constructed. Simultaneously, the signal transmission requirements of each component (such as...) are analyzed. The wiring harness layout should be determined by considering factors such as PWM signals for flight control and servos, RF signals for communication modules, and current load parameters (e.g., high-current loops, low-current loops). Spatial constraints (e.g., avoiding moving parts like propellers and servos) and performance requirements (e.g., vibration resistance, high-temperature resistance, flame retardancy) should be clearly defined. Next, wiring harness routing should be planned, selecting pre-reserved wiring channels within the fuselage or non-critical load-bearing areas (e.g., fuselage frame sandwich structures, wing leading edge cavities). Anti-interference principles should be followed (e.g., separation of strong and weak currents, keeping signal harnesses away from power harnesses and RF antennas). Routing optimization algorithms (e.g., A / B) should be used. The algorithm (such as Dijkstra's algorithm) is used to iteratively calculate and determine the shortest wiring path that avoids obstacles, while marking key nodes on the path (such as vias, turns, etc.). Then, the wiring harness is selected based on the wiring path parameters and performance requirements, and the insulation material is selected according to environmental requirements (such as using fluoroplastic insulated wire in high-temperature areas). After that, the UAV wiring harness is fixed based on the wiring path to ensure that the wiring harness does not shift or wear under flight vibration environment, and finally the layout scheme is finalized.

[0003] In the wiring harness layout process of UAVs, existing technologies first determine the function of each group of wiring harnesses, dividing the system wiring harnesses within each subsystem into functional wiring harnesses with different functions (such as power supply signal modules, analog signal modules, communication signal modules, etc.); then, based on the actual state of each functional wiring harness, the cable length and cross-linking portion are confirmed, forming cross-linked wiring harnesses of different lengths, and the cross-linking lengths of various cross-linked wiring harnesses are counted and sorted from longest to shortest; furthermore, signal processing and electromagnetic interference protection are performed on the cross-linked wiring harnesses; finally, the matching parameters between the anti-interference wiring harnesses and the equipment (such as distance, equipment location, wiring harness model, etc.) are obtained, and a layout simulation model is established with the available wiring space as a constraint. Based on the distance between the wiring harness and the corresponding equipment, wiring harness path optimization is performed to obtain multiple wiring harness layout schemes. At least two schemes with the fewest entanglement and winding times or the smallest total length are selected from the multiple wiring harness layout schemes for manual evaluation. After determining the final scheme, each group of anti-interference wiring harnesses is marked, a fixing device is determined, and the layout structure is clarified until the set complete ring structure layout is completed.

[0004] For example, Chinese invention patent application CN114572404A discloses a radio receiver that is mounted on the energy absorption device of a parachute for aircraft and drones. The receiver includes: connecting a wire harness with a retaining pin to a special spool of the radio-controlled energy absorption device, ensuring that one end of the wire harness is securely connected to the retaining pin, and the other end is wound in an orderly manner on the spool, forming a wire harness transmission structure that can transmit tension through the rotation of the spool. At the same time, the device is assembled between the main control belt and the suspension belt of the aircraft or drone parachute, completing the connection and deployment of the wire harness, the device, and the parachute system.

[0005] The above-mentioned technology has at least the following technical problems:

[0006] In the process of wiring harness layout and signal transmission for multi-device integrated UAVs, existing methods often rely on semi-automatic path allocation based on simple geometric rules when wiring harnesses are laid out in high-density areas such as equipment compartments. This lacks the ability to globally optimize for the complex electromagnetic environment of multiple devices, resulting in layout defects such as wiring harness overlap and chaotic path planning. This leads to electromagnetic coupling interference (such as current intensity and signal frequency) between UAV wiring harnesses. Due to electromagnetic coupling interference, navigation and image link signals may become unstable, ultimately leading to a decrease in the stability of the UAV monitoring network data link and a problem of low data transmission stability in the UAV monitoring network. Summary of the Invention

[0007] This invention provides a method, system, and medium for laying out UAV wiring harnesses, which solves the problem of low data transmission stability in UAV monitoring networks in the prior art and improves the stability of UAV monitoring network data links.

[0008] To achieve the above-mentioned objectives, the present invention provides the following technical solution:

[0009] On one hand, a method for UAV wiring harness layout is provided. This method includes: during the UAV wiring harness layout process, performing an electromagnetic coupling interference assessment of the UAV wiring harness; based on the obtained electromagnetic coupling interference assessment results, determining whether magnetic field interference suppression and electric field interference suppression are necessary. Magnetic field interference suppression is used in the UAV wiring harness layout to weaken the mutual inductive coupling between the low-frequency high-current wiring harness and the core control signal line by optimizing the truncated parallel segments and turning angles; electric field interference suppression is used in the UAV wiring harness layout to reduce capacitive coupling between the high-frequency high-voltage wiring harness and the weak signal line by adjusting the safety distance between them. If the UAV wiring harness electromagnetic coupling interference assessment is qualified... If the signal fluctuation is high, an analysis of the UAV signal fluctuation is performed; otherwise, a statistical quantification of the UAV harness crossing is performed to accurately quantify the density of harness crossings and the degree of electromagnetic risk superposition. Based on the obtained statistical quantification results of the UAV harness crossing, it is determined whether harness layout adjustment is necessary. Harness layout adjustment is used to optimize harness paths according to interference priority, and improve the electromagnetic compatibility and spatial rationality of the harness layout. After the statistical quantification of the UAV harness crossing is completed, an analysis of the UAV signal fluctuation is performed to evaluate the stability of the harness signal and the degree of interference impact. Based on the obtained UAV signal fluctuation analysis results, it is determined whether a signal fluctuation anomaly alarm needs to be sent.

[0010] On one hand, a UAV harness layout system is provided, which applies a UAV harness layout method, including: an electromagnetic coupling interference monitoring module, a UAV harness crossing situation monitoring module, and a signal fluctuation monitoring module. The electromagnetic coupling interference monitoring module is used to evaluate the electromagnetic coupling interference of the UAV harness during the harness layout process, and determines whether magnetic field interference suppression and electric field interference suppression are needed based on the obtained evaluation results. The UAV harness crossing situation monitoring module is used to analyze the UAV signal fluctuation if the electromagnetic coupling interference evaluation is qualified; otherwise, it performs statistical quantification of the UAV harness crossing situation to accurately quantify the harness crossing density and the degree of electromagnetic risk superposition. Based on the obtained statistical quantification results, it determines whether harness layout adjustments are needed. The signal fluctuation monitoring module is used to analyze the UAV signal fluctuation after the statistical quantification of the UAV harness crossing situation, to evaluate the harness signal stability and the degree of interference impact, and determines whether a signal fluctuation anomaly alarm needs to be sent based on the obtained analysis results.

[0011] On the other hand, a drone harness layout medium is provided, which is applied as a drone harness layout method. The drone harness layout medium stores program code that can be called by a processor to execute any of the methods in the drone harness layout method.

[0012] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0013] 1. By conducting an electromagnetic coupling interference assessment of the UAV wiring harness, the results are used to determine whether magnetic field interference suppression and electric field interference suppression are necessary. This helps to reduce the electromagnetic coupling interference between low-frequency high-current wiring harnesses and high-frequency high-voltage wiring harnesses on core signal lines within the UAV equipment cabin, laying the foundation for stable transmission of core signals. If the UAV wiring harness electromagnetic coupling interference assessment is satisfactory, UAV signal fluctuation analysis is performed. Otherwise, statistical quantification of UAV wiring harness crossing is conducted to accurately quantify the density of wiring harness crossings and the degree of electromagnetic risk superposition. Based on the obtained statistical quantification results of UAV wiring harness crossing, the need for further measures is determined. Adjusting the wiring harness layout helps reduce the superposition of electromagnetic risks caused by excessive wiring harness crossing, improves the electromagnetic compatibility and spatial rationality of the UAV wiring harness layout. After the statistical quantification of UAV wiring harness crossing, an analysis of UAV signal fluctuations is conducted to assess the stability of wiring harness signals and the degree of interference. Based on the obtained UAV signal fluctuation analysis results, it is determined whether to send a signal fluctuation anomaly alarm. This helps to promptly identify signal amplitude anomalies caused by factors such as residual electromagnetic interference and poor wiring harness contact, reducing the impact of signal fluctuations on core functions such as autonomous flight and precise hovering of UAVs, and providing signal reliability assurance for the safe and stable execution of UAV missions.

[0014] 2. By selectively choosing the contribution of intersection points, overlap, mutual inductance, and coupling capacitance as multi-dimensional data items for quantifying harness layout deviations, this approach comprehensively captures the deviation states in different dimensions of UAV harness layouts, such as the density of intersection distribution, the scale of overlapping areas, and the risks of magnetic and electric coupling. This avoids the limitation of a single parameter only assessing one dimension of layout deviation, effectively filling the technical gap in existing technologies that can only assess spatial characteristics of the layout and cannot globally correlate electromagnetic interference risks. The result of weighted coupling of the harness layout deviation quantification data items and the corresponding local harness deviation weight parameters serves as the harness layout deviation quantification index, comprehensively considering the impact of different dimensional deviations on the overall layout. By considering the combined effects of various factors, this approach avoids biases caused by evaluating a single data item. It allows for a more objective reflection of the overall impact of individual harness layout deviations on the global layout. The system determines whether the total number of harness layout deviations exceeds a preset threshold. If so, harness layout adjustments are made; otherwise, UAV signal fluctuation analysis is conducted. This helps to specifically address electromagnetic coupling risks caused by layout deviations, avoiding blind adjustments or ignoring the impact of deviations on signal transmission. It effectively solves the problem of new layout conflicts arising from the use of single parameters for layout adjustments in existing technologies, ensuring the stability of core signal transmission and providing a reliable harness layout foundation for subsequent UAV signal fluctuation analysis.

[0015] 3. By selectively choosing the signal amplitude variation coefficient, phase jitter normalized value, and autocorrelation coefficient attenuation value as multi-dimensional interference fluctuation characteristic parameters, this approach can comprehensively capture the stability of UAV harness signals in different dimensions such as amplitude, phase, and fluctuation patterns under strong electromagnetic environments. This avoids the limitation of a single parameter only evaluating one dimension of signal fluctuation, effectively filling the technical gap in existing technologies that can only evaluate one dimension of signal fluctuation and easily miss potential phase distortion or abnormal fluctuation trends. The result of weighted coupling processing of the interference fluctuation characteristic parameters and their influence values ​​is used as the UAV signal fluctuation index. This comprehensively considers the influence weight of fluctuation characteristics in each dimension on the overall signal stability, avoiding bias caused by single-parameter evaluation, and making the signal fluctuation index more comprehensive. This solution provides a more objective reflection of the interference level and overall stability of UAV wiring harness signals in strong electromagnetic environments. Furthermore, existing signal alarm mechanisms, often based on a single parameter threshold, are prone to blind alarms or missed alarms. In contrast, this solution determines whether the UAV signal fluctuation index exceeds a preset signal fluctuation threshold. If so, an abnormal signal fluctuation alarm is sent; otherwise, the signal fluctuation is considered normal, and continuous monitoring is performed. This helps to specifically identify abnormal signal fluctuations, avoid blind alarms or ignoring potential interference risks, and provide timely warnings for signal fluctuations exceeding the preset threshold. This ensures the reliability of UAV core wiring harness signal transmission and provides precise signal-level monitoring and risk control support for the safe and stable execution of flight missions by UAVs in strong electromagnetic environments. Attached Figure Description

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

[0017] Figure 1 is a flowchart of a UAV wiring harness layout method provided in an embodiment of the present invention;

[0018] Figure 2 is a general overview diagram of a UAV wiring harness layout method provided in an embodiment of the present invention;

[0019] Figure 3 is a statistical quantification logic diagram of the UAV wiring harness crossing situation of a UAV wiring harness layout method provided in an embodiment of the present invention.

[0020] Figure 4 is a structural schematic diagram of a UAV wiring harness layout system provided in an embodiment of the present invention. Detailed Implementation

[0021] 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, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0022] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms “first,” “second,” and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Similarly, the terms “an,” “a,” or “the,” and similar terms do not indicate a quantity limitation, but rather indicate the presence of at least one. The terms “comprising,” “including,” or “including,” and similar terms mean that the element or object preceding the word encompasses the element or object listed following the word and its equivalents, without excluding other elements or objects. The terms “connected,” “linked,” or “connected,” and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect.

[0023] It should be noted that the terms "up", "down", "left", "right", "front", and "back" used in this invention are only used to indicate relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0024] Figure 1 shows a flowchart of a UAV wiring harness layout method provided in this application embodiment. The UAV wiring harness layout method includes: First, electromagnetic coupling interference monitoring. During the UAV wiring harness layout process, an electromagnetic coupling interference assessment of the UAV wiring harness is performed. Based on the obtained assessment results, it is determined whether magnetic field interference suppression and electric field interference suppression are required. Magnetic field interference suppression is used in the UAV wiring harness layout to weaken the mutual inductive coupling between the low-frequency high-current wiring harness and the core control signal line by optimizing the truncated parallel segments and turning angles, reducing the impact of magnetic field interference on the stability of key signal transmission, and reducing command delays and navigation signal drift caused by unreasonable layout. Electric field interference suppression is used in the UAV wiring harness layout to reduce capacitive coupling between the high-frequency high-voltage wiring harness and the weak signal line by adjusting the safety distance, reducing signal amplitude and phase distortion caused by electric field induced noise, and ensuring the signal integrity required for UAV mission execution. Electromagnetic coupling interference monitoring helps to prevent electromagnetic coupling risks from the source of UAV wiring harness layout, specifically weakening the interference of low-frequency magnetic fields and high-frequency electric fields on core signals, reducing signal transmission risks caused by layout defects, and ensuring signal support for the core functions of the UAV.

[0025] Secondly, monitoring the crossover of UAV harnesses is crucial. If the electromagnetic coupling interference assessment of the UAV harnesses is satisfactory, then the signal fluctuation of the UAV is analyzed. Otherwise, statistical quantification of the crossover of UAV harnesses is performed to accurately quantify the density of crossover and the degree of electromagnetic risk superposition. Based on the obtained statistical quantification results of the UAV harness crossover, it is determined whether harness layout adjustments are necessary. Harness layout adjustments are used to optimize harness paths according to interference priority, improving the electromagnetic compatibility and spatial rationality of the harness layout. Monitoring the crossover of UAV harnesses helps to accurately locate the electromagnetic risk superposition area caused by excessive crossover, reducing the spread of interference source harnesses through densely crossed areas and affecting more interfered harnesses. This achieves a balance between electromagnetic compatibility and space utilization in the compact equipment compartment space of the UAV.

[0026] Finally, signal fluctuation monitoring is performed. After the statistical quantification of the UAV harness crossing situation, UAV signal fluctuation analysis is conducted to assess the stability of the harness signal and the degree of interference. Based on the obtained UAV signal fluctuation analysis results, it is determined whether to send a signal fluctuation anomaly alarm. Signal monitoring helps to promptly identify signal anomalies caused by residual electromagnetic interference or sudden interference after the optimization of the UAV harness layout, reducing the impact of signal fluctuation on core tasks such as autonomous flight, precise hovering, and mission data transmission of UAVs, and improving the stability of the UAV monitoring network data link.

[0027] It is important to note that the UAV harness layout method provided in this application establishes a database storing various preset data before design. The data sources of this database include not only basic preset values ​​such as preset radiation thresholds, preset harness deviation thresholds, and preset signal fluctuation thresholds directly set by technicians, but also reference datasets compiled from historical UAV flight cases (such as harness layout data and signal fluctuation records under different electromagnetic environments) and electromagnetic interference experimental data (such as coupling coefficient test results and cross-risk verification data under multiple scenarios). This provides practical support for the rationality of the preset values. Its storage adopts an encrypted distributed architecture, combining a relational database to store structured preset parameters (such as the specific values ​​of various thresholds and the value range of weight factors) and a non-relational database to store unstructured reference data (such as three-dimensional harness layout maps and signal fluctuation time-series curves from historical flights). Technicians can dynamically calibrate the preset values ​​based on newly accumulated UAV flight data and electromagnetic environment feedback, so that the stored data always adapts to the actual UAV operation scenario requirements.

[0028] In this embodiment, a comprehensive system for ensuring the electromagnetic interference and signal reliability of UAV harnesses is constructed through electromagnetic coupling interference monitoring, UAV harness crossing monitoring, and signal fluctuation monitoring. This system covers the entire process from source interference prevention and control, intermediate layout optimization, to terminal signal early warning. Electromagnetic coupling interference monitoring specifically weakens the mutual inductive coupling between low-frequency high-current harnesses and core control lines, and the capacitive coupling between high-frequency high-voltage harnesses and weak signal lines from the source of the layout, reducing signal transmission risks caused by initial layout defects. UAV harness crossing monitoring further addresses the problem of electromagnetic risk superposition caused by harness crossings. By quantifying the crossing density and risk level and optimizing the path, electromagnetic compatibility and space utilization are balanced within the compact equipment cabin space of the UAV. Signal fluctuation monitoring promptly identifies residual electromagnetic interference after previous optimization or signal anomalies caused by sudden interference. The three systems work together to effectively reduce problems such as command delay, navigation signal drift, and distortion of mission data (such as images and sensor information) transmission caused by electromagnetic interference.

[0029] Figure 2 shows an overall overview of a UAV harness layout method provided in this application embodiment. As shown in Figure 2, the following steps are performed: Electromagnetic coupling interference evaluation of the UAV harness is conducted, and the signal frequency corresponding to the interference source harness in the harness pair matrix is ​​obtained. It is determined whether the signal frequency is less than a preset signal frequency. If so, magnetic field coupling interference analysis is performed; otherwise, electric field coupling interference analysis is performed. After magnetic field coupling interference analysis, magnetic field coupling interference determination is performed. If the magnetic field coupling interference determination is qualified, UAV signal fluctuation analysis is performed; otherwise, harness pair magnetic field interference marking is performed, and it is determined whether the magnetic field marking counter value is greater than a preset maximum magnetic field interference harness pair threshold. If not, the UAV harness electromagnetic coupling interference evaluation continues; otherwise, magnetic field interference suppression is implemented, and the magnetic field harness pair interference suppression effect is determined. If the magnetic field coupling interference determination is qualified, the UAV... If the signal fluctuation is normal, then the system performs statistical quantification of the UAV harness crossing situation, performs electric field coupling interference analysis, and then determines the electric field coupling interference. If the electric field coupling interference determination is qualified, then the UAV signal fluctuation is analyzed; otherwise, the harness is marked for electric field interference, and it is determined whether the electric field mark counter value is greater than the preset maximum threshold for electric field interference times. If not, then the electric field coupling interference analysis continues; otherwise, electric field interference suppression is implemented. After the electric field interference suppression is completed, the electric field coupling interference is determined. If the electric field coupling interference determination is unqualified, then the UAV harness crossing situation is statistically quantified; otherwise, the UAV signal fluctuation is analyzed, and the amplitude fluctuation coefficient is obtained. It is determined whether the amplitude fluctuation coefficient is less than the preset amplitude fluctuation threshold. If so, then the signal fluctuation is determined to be normal, and continuous monitoring is performed; otherwise, an abnormal signal fluctuation alarm is sent.

[0030] Preferably, the UAV wiring harness electromagnetic coupling interference assessment is used to evaluate the electromagnetic coupling risks generated during the layout of different functional wiring harnesses within the UAV equipment compartment, ensuring the stability of the UAV's core signal transmission. The specific process is as follows: Wiring harness matrix generation: All wiring harnesses within the UAV equipment compartment are numbered to obtain a unique ID number corresponding to each UAV wiring harness (e.g., wiring harness 1: flight control power cable, wiring harness 2: GPS signal cable, wiring harness 3: image transmission cable...).), and generate a wire harness pair matrix containing wire harness pairs based on the permutation and combination algorithm; monitor the signal frequency corresponding to the interfering source wire harness in the wire harness pair matrix. When the corresponding signal frequency is less than the preset signal frequency, magnetic field coupling interference analysis is performed. Otherwise, electric field coupling interference analysis is performed, where the preset signal frequency is represented by the average value of the signal frequencies in the historical time period; the interfering source wire harness refers to the wire harness that can generate electromagnetic interference in each pair of interacting wire harnesses; the specific process of magnetic field coupling interference analysis is as follows: input the current intensity, signal frequency, and wire harness pair spacing value of the interfering source wire harness into the preset mutual inductance coupling model for coupling strength calculation, output the corresponding mutual inductance coefficient and induced interference voltage, and perform magnetic field coupling interference determination for discriminating the magnetic field coupling risk caused by low-frequency high-current wire harnesses and ensuring the transmission stability of core signal wires such as flight control and navigation. If the magnetic field coupling interference determination is qualified, analyze the signal fluctuation situation of the UAV. Otherwise, perform wire harness pair magnetic field interference marking for recording the number of interfering source wire harnesses of the UAV with magnetic field coupling risk, where the current intensity is monitored by a Hall current sensor, the signal frequency is monitored by a spectrum analyzer, and the wire harness pair spacing value is represented by the shortest spatial distance obtained by performing spatial Euclidean distance calculation on the central axis coordinates of the two wire harnesses acquired by a three-dimensional scanner inside the UAV equipment cabin; the wire harness pair magnetic field interference marking means adding 1 to the value of the magnetic field marking counter, storing the corresponding interfering source wire harness numbers in sequence in the preset magnetic field interference database, and at the same time judging whether the value of the magnetic field marking counter is greater than the preset maximum wire harness pair threshold of magnetic field interference. If so, take magnetic field interference suppression and reset the value of the corresponding magnetic field marking counter to the initial value. Otherwise, continue to execute the electromagnetic coupling interference evaluation of the UAV wire harness. The preset magnetic field interference database is set in advance by the preset personnel; the preset maximum wire harness pair threshold of magnetic field interference is represented by the average value of the number of wire harness pairs with unqualified magnetic field coupling interference determination in the historical time period; the preset mutual inductance coupling model is set in advance by the preset personnel and is used to quantify the magnetic field coupling effect between two wire harnesses in the low-frequency scenario. The mutual inductance coefficient is used to reflect the tightness of the magnetic field coupling between the two wire harnesses, and the induced interference voltage is used to reflect the interference intensity of the interfering source wire harness on the interfered wire harness; the specific process of magnetic field coupling interference determination is as follows: judge whether the mutual inductance coefficient is less than the preset minimum mutual inductance coefficient threshold and whether the induced interference voltage is less than the preset minimum induced interference voltage threshold. If so, it is determined that the magnetic field coupling interference determination is qualified. Otherwise, it is determined that the magnetic field coupling interference determination is unqualified, where the preset minimum mutual inductance coefficient threshold is represented by the average value of the mutual inductance coefficients in the historical time period, and the preset minimum induced interference voltage threshold is represented by the average value of the induced interference voltages in the historical time period.

[0031] Specifically, the process of electric field coupling interference analysis is as follows: The voltage of the interference source bundle, signal frequency, and the bundle pair spacing are input into a preset capacitive coupling model to calculate the coupling strength. The coupling capacitance and noise voltage of the corresponding bundle pair are output. An electric field coupling interference judgment is then performed to identify the risk of electric field coupling caused by the high-frequency, high-voltage bundle. If the electric field coupling interference judgment is successful, the UAV signal fluctuation is analyzed; otherwise, a bundle pair electric field interference marker is used to record the number of times the corresponding interference source bundle's electric field coupling interference judgment fails. The voltage of the interference source bundle is monitored by a high-voltage sensor. The bundle pair electric field interference marker increments the electric field marker counter value of the corresponding interference source bundle by 1 and checks whether the electric field marker counter value is greater than the preset maximum electric field interference threshold. If it is, electric field interference suppression is implemented, and the corresponding electric field marker counter value is reset to its initial value; otherwise... If the electric field coupling interference analysis continues, the preset maximum electric field interference threshold is represented by the average value of the wires that failed the electric field coupling interference judgment over a historical time period. The preset capacitance coupling model is set in advance by preset personnel to quantify the electric field coupling effect between two wires in high-frequency scenarios. The coupling capacitance is used to reflect the strength of electric field coupling between the two wires, and the noise voltage is used to reflect the amplitude of the signal influence of the interference source wire on the interference wire. The specific process of electric field coupling interference judgment is as follows: it is determined whether the coupling capacitance is less than the preset minimum coupling capacitance threshold and whether the noise voltage is less than the preset minimum noise voltage threshold. If so, the electric field coupling interference judgment is deemed qualified; otherwise, it is deemed unqualified. The preset minimum coupling capacitance threshold is represented by the average value of the coupling capacitance over a historical time period, and the preset minimum noise voltage threshold is represented by the average value of the noise voltage over a historical time period.

[0032] In this embodiment, an electromagnetic risk pre-assessment system based on harness pair matrix and frequency-specific differential analysis was constructed through electromagnetic coupling interference assessment of UAV harnesses. This system helps to specifically identify the mutual inductive coupling risks between low-frequency high-current harnesses and core harnesses, and the capacitive coupling risks between high-frequency high-voltage harnesses and weak signal lines. This reduces electromagnetic risks hidden in later flight operations and minimizes problems such as command delays, navigation signal drift, signal amplitude distortion, and phase shift caused by magnetic field interference. It also improves the stability and reliability of UAV core signal line transmission and achieves closed-loop management from harness pair coupling strength calculation and risk assessment to marking unqualified harness pairs and triggering interference suppression measures, ensuring the stability of UAV mission data transmission.

[0033] Preferably, the specific process of magnetic field interference suppression is as follows: The interference source bundle numbers are retrieved sequentially from a preset magnetic field interference database, and the bundle pairs corresponding to these interference source bundle numbers are subjected to magnetic field bundle pair interference suppression. The specific process of magnetic field bundle pair interference suppression is as follows: Based on a multi-objective optimization algorithm (such as the NSGA-II algorithm, MOPSO algorithm, etc.), the optimization parameters for truncated parallel segments are obtained. These parameters include the maximum parallel length of a single segment, the minimum turning angle, the safety distance, and the density of fixed points. Based on a path splitting algorithm (such as a greedy splitting algorithm, etc.) and the optimization parameters for truncated parallel segments, turning node planning and path splitting are performed to obtain the bundle segment path planning results. These results include the coordinates of the bundle turning nodes, the turning angle, and the coordinates of the start and end points of each segment. Based on an interpolation algorithm (such as linear interpolation, cubic spline interpolation, etc.), the completeness of each segment after turning node planning and path splitting is obtained. The complete set of wiring coordinates is used to adjust the wiring harness segments. This complete set of coordinates accurately describes the three-dimensional spatial orientation of the adjusted wiring harness within the UAV's equipment compartment, ensuring that each segment strictly adheres to the optimized parameters for truncated parallel segments. This weakens the magnetic field coupling effect between the interference source and the interfered wiring harness by shortening the length of the parallel segments and increasing the spatial distance. The interference suppression effect of the magnetic field wiring harness is then assessed: a new magnetic field coupling interference assessment is performed. If the assessment is satisfactory, UAV signal fluctuation analysis is conducted; otherwise, statistical quantification of UAV wiring harness crossover is performed. After the current magnetic field wiring harness interference suppression ends, wiring harness pair numbers are retrieved sequentially from the preset magnetic field interference database. If the database is not empty, magnetic field interference suppression is applied; otherwise, the database is cleared, ending the current round of magnetic field interference suppression.

[0034] In this embodiment, by suppressing magnetic field interference, the inefficiency caused by blindly adjusting all UAV wiring harnesses is reduced. This allows for targeted intervention of wiring harness pairs at risk of magnetic field coupling. Simultaneously, it ensures that wiring harness adjustments comply with the spatial constraints of the UAV equipment bay, and by shortening the parallel segment length of the interference source and the interfered wiring harness and increasing the spatial spacing, it precisely weakens the mutual inductance coupling effect from a physical layout perspective. This effectively reduces the magnetic field interference of low-frequency high-current wiring harnesses on core signal lines, reducing problems such as command delays and navigation signal drift caused by magnetic field coupling. It ensures that all preset risk wiring harness pairs are effectively handled, providing a guarantee for the stable transmission of core signals in low-frequency, strong electromagnetic environments, and improving the electromagnetic compatibility of the UAV wiring harness layout and the reliability of flight mission execution.

[0035] Preferably, the specific process of electric field interference suppression is as follows: The coupling capacitance and noise voltage are queried from the beam amplification distance coefficient mapping set to obtain the target amplification distance coefficient; using the adjustment amplitude corresponding to the target amplification distance coefficient as the adjustment step size, the actual distance between the two beams is adjusted step-by-step in the direction of increasing beam spacing (after each adjustment of the actual distance between the two beams is completed, the coupling capacitance and noise voltage are re-acquired and electric field coupling interference is judged; if the electric field coupling interference judgment is unqualified, the actual distance between the two beams after this adjustment is used as the initial value for the next adjustment and the adjustment continues step-by-step in the direction of increasing beam spacing). This helps to adapt to the compact space constraints of the UAV equipment cabin and avoids large-scale adjustments at once. This approach avoids wasting space or squeezing other wiring harness layouts, ensuring effective electric field interference suppression while preventing excessive adjustments that could lead to new layout conflicts, thus improving the reliability and space utilization of spacing adjustments. The adjusted spacing increment is then added to the current actual spacing between the wiring harnesses. The system continuously monitors coupling capacitance and noise voltage and performs electric field coupling interference judgment. If the judgment is satisfactory, the system analyzes the UAV signal fluctuations; otherwise, it continues to suppress electric field interference. If the number of electric field interference suppression executions exceeds the preset maximum execution threshold, and the judgment is deemed unsatisfactory, the system performs statistical quantification of UAV wiring harness crossovers. The preset maximum execution threshold for electric field interference suppression is pre-set by designated personnel.

[0036] It is important to note that the beam amplification distance coefficient mapping set involved in electric field interference suppression is pre-set and stored in a database by professional technicians. This provides a precise matching basis for coupling capacitance, noise voltage, and target amplification distance coefficient. For example, a large amount of historical data under high-frequency electric field coupling scenarios of UAVs is extracted, covering parameter combinations of different coupling capacitances, noise voltages, and corresponding effective amplification distance coefficients. Each parameter combination is assigned a quantitative value based on its adaptability to electric field interference suppression (e.g., when the coupling capacitance value is high, a larger amplification distance coefficient is matched to ensure effective reduction of capacitive coupling; when the noise voltage slightly exceeds the threshold, a moderate amplification distance coefficient is matched to avoid over-adjustment). The system records the actual effective values ​​of the target amplification distance coefficient under each historical scenario. Then, through correlation analysis (such as Spearman correlation coefficient), abnormal correlation data caused by temporary equipment failures (such as voltage sensor malfunctions) or sudden fluctuations in the electromagnetic environment (such as instantaneous high-frequency interference) are eliminated. The system retains the correspondence between statistically significant parameter combinations and amplification distance coefficients. Finally, all effective data are integrated to form a harness amplification distance coefficient mapping set containing multiple mapping relationships. When the system performs electric field interference suppression, the matching target amplification distance coefficient can be quickly retrieved from this mapping set to ensure the accuracy of the spacing adjustment range and avoid poor suppression effect or waste of space resources caused by blindly setting adjustment values.

[0037] In this embodiment, by suppressing electric field interference, the problem of blindly setting the adjustment range is solved. It can accurately find the minimum spacing that meets the qualified standard within the compact equipment compartment of the UAV, and ensure that each adjustment is supported by actual data, thereby improving the reliability of electric field interference suppression. It effectively weakens the capacitive coupling effect between the high-frequency high-voltage harness and the weak signal line, reduces signal amplitude distortion and phase shift caused by electric field induced noise, and ensures the integrity of weak signals required for UAV inspection image acquisition, environmental data monitoring and other tasks. It lays a stable signal foundation for subsequent analysis of UAV signal fluctuations, and further improves the electric field compatibility of the UAV harness layout and the stability of core task execution.

[0038] As shown in Figure 3, the present application provides a method for the statistical quantification of drone harness crossover in an embodiment of the drone harness layout. As shown in Figure 3, the drone harness crossover is statistically quantified, and the total number of harness layout deviations is obtained. It is then determined whether the total number of harness layout deviations is greater than a preset harness layout deviation threshold. If not, the drone signal fluctuation is analyzed; otherwise, the harness layout is adjusted. After the harness layout adjustment is completed, it is determined whether the statistical quantification of drone harness crossover is qualified. If not, a harness layout adjustment failure alarm is sent; otherwise, the drone signal fluctuation is analyzed.

[0039] Preferably, the specific process for statistical quantification of UAV harness crossing is as follows: Obtain harness layout deviation quantification data items to assess the severity of UAV harness crossing; these data items include: a crosspoint contribution to quantify the frequency of a single harness crossing, reflecting the density of the crosspoint distribution in the overall layout; an overlap contribution to quantify the actual length ratio of a single harness crossing and reflecting the effective overlap area between the harness and other harnesses; a mutual inductance contribution to quantify the risk of magnetic field coupling caused by a single harness crossing with other harnesses, relating to the influence of mutual inductance coefficient on core signal transmission interference; and a coupling capacitance contribution to quantify the risk of electric field coupling caused by a single harness crossing with other harnesses, relating to the influence of coupling capacitance on weak signal noise superposition. The contribution of crossover points is represented by the ratio of the number of crossover points of a single harness to the total number of crossover points of harnesses in the UAV equipment compartment. The number of crossover points of a single harness is represented by the result of the cumulative calculation of the crossover points formed by the harness with all other harnesses in the equipment compartment by the crossover point counter. The crossover point is represented by the coordinates of the harness center axis extracted by the 3D scanner, and the shortest spatial distance between the harness pairs in the harness pair matrix is ​​calculated based on Euclidean distance (when the shortest spatial distance is less than the preset crossover distance threshold, it is determined as 1 crossover point). A single harness is represented by a harness in the UAV equipment compartment. The total number of crossover points of harnesses in the UAV equipment compartment is represented by the cumulative result of the number of crossover points of all single harnesses in the UAV equipment compartment. The ratio quantification is represented by the ratio calculation, and the preset crossover distance threshold is set in advance by preset personnel.

[0040] Specifically, the overlap contribution is represented by quantifying the ratio of the individual wire bundle cross-overlap length to the total wire bundle cross-overlap length. The individual wire bundle cross-overlap length is represented by summing the lengths of continuous line segments of the wire bundles that meet the cross-overlap length condition. The cross-overlap length condition means that the spatial distance between the wire bundles is less than a preset cross-over distance threshold and the length of the continuous line segments is greater than a preset cross-over line segment length threshold. The length of the continuous line segments is represented by extracting the start and end coordinates of the continuous line segments that meet the condition of the spatial distance between the wire bundles being less than the preset cross-over distance threshold from the axes of the two crossing wire bundles, and then performing spatial processing on the start and end coordinates. Spatial processing means performing three-dimensional Euclidean distance calculation. The total wire bundle cross-overlap length is represented by summing the individual wire bundle cross-overlap lengths of all wire bundles in the UAV equipment cabin. The following parameters are defined: The spatial distance between the wire harness pairs is represented by the shortest spatial distance calculated using the coordinates of the center axes of the two wire harnesses extracted by the 3D scanner inside the UAV equipment cabin, and the preset threshold for the length of the intersecting line segments is pre-set by a pre-defined team. Mutual inductance contribution is represented by the ratio of the total mutual inductance coefficient of a single wire harness to the statistical value of mutual inductance coefficients. The total mutual inductance coefficient of a single wire harness is represented by the sum of the mutual inductance coefficients between the single wire harness and all associated wire harnesses. The statistical value of mutual inductance coefficients is represented by the sum of the mutual inductance coefficients of all wire harness pairs. The coupling capacitance contribution is represented by the ratio of the total coupling capacitance of a single wire harness to the statistical value of coupling capacitance. The total coupling capacitance of a single wire harness is represented by the sum of the coupling capacitances between the single wire harness and all associated wire harnesses. The statistical value of coupling capacitance is represented by the average value of the coupling capacitances of all wire harness pairs.

[0041] Specifically, the result of weighted coupling processing of the local deviation data items of the harness and the corresponding local deviation weight parameters is used as a quantitative index of harness layout deviation to characterize the comprehensive influence of a single harness on the global layout deviation. The weighted coupling processing involves first multiplying the local deviation data items of the harness with the corresponding local deviation weight parameters (crosspoint contribution weight factor, overlap contribution weight factor, mutual inductance contribution weight factor, and coupling capacitance contribution weight factor), obtaining the single-item product result, and then... The process of accumulating the results of individual product operations; when the contribution of the intersection point increases, it indicates that the number of intersections between a single wire harness and other wire harnesses in the UAV equipment compartment increases, and the density of the intersection distribution increases. The increase in the density of the intersection increases the probability of forming an effective overlapping area between wire harnesses, which in turn leads to an increase in the overlap contribution. When the overlap contribution increases, it indicates that the expansion of the overlapping area will shorten the actual action distance between wire harnesses, which will enhance the electric and magnetic field coupling effect with the interfered wire harness, leading to an increase in the mutual inductance contribution and coupling capacitance contribution. The overall increase in the local deviation data item of the wire harness will lead to an increase in the quantitative index of wire harness layout deviation.

[0042] Specifically, the local deviation weight parameters for the wiring harness include a cross-point contribution weight factor reflecting the influence of cross-point contribution on the quantitative index of wiring harness layout deviation, an overlap contribution weight factor reflecting the influence of overlap contribution on the quantitative index of wiring harness layout deviation, a mutual inductance contribution weight factor reflecting the influence of mutual inductance contribution on the quantitative index of wiring harness layout deviation, and a coupling capacitance contribution weight factor reflecting the influence of coupling capacitance contribution on the quantitative index of wiring harness layout deviation. The system determines whether the total number of wiring harness layout deviations exceeds a preset wiring harness layout deviation threshold. If so, wiring harness layout adjustments are made; otherwise, UAV signal fluctuation analysis is performed. The preset wiring harness layout deviation threshold is represented by the average of the total number of wiring harness layout deviations over a historical time period. The total number of wiring harness layout deviations represents the total number of UAV wiring harnesses that meet the wiring harness deviation determination criteria. The wiring harness deviation determination criteria indicate that the quantitative index of wiring harness layout deviation exceeds the preset wiring harness deviation threshold, which is also represented by the average of the quantitative index of wiring harness layout deviation over a historical time period.

[0043] It is important to note that the statistical quantification of drone harness crossing situations involves a set of weighted parameter mappings used to quantify the influence of crossover contribution weight factors, overlap contribution weight factors, mutual inductance contribution weight factors, and coupling capacitance contribution weight factors on the harness layout deviation quantification index. This set is pre-set by technical personnel and stored in a database, providing a basis for matching harness local deviation data items with their corresponding harness local deviation weight parameters. For example, a large amount of historical data from drone harness layout scenarios is extracted, covering parameter combinations of crossover contribution, overlap contribution, mutual inductance contribution, coupling capacitance contribution, and corresponding harness local deviation weight parameters under different operating conditions. Each parameter combination is assigned a weighted quantification value based on its influence on the harness layout deviation quantification index, and the four weights are recorded simultaneously for each historical scenario. The actual effective values ​​of the weighted factors are then analyzed using correlation analysis (such as Spearman correlation coefficient) to eliminate abnormal correlation data caused by temporary equipment failures (such as abnormal accuracy of 3D scanners) or sudden deviations in wire harness installation (such as loose wire harness fixing clips). The correspondence between statistically significant parameter combinations and weighted factors is retained. Finally, all effective data are integrated to form a weighted parameter mapping group containing multiple mapping relationships. The correlation correspondence rules within the mapping group use a numerical range of 0-1 to represent the influence ratio of each weighted factor. This achieves a one-to-one mapping or many-to-one adaptation effect between each basic contribution data item and the corresponding weighted factor in the quantitative analysis of wire harness layout deviation. When the system performs quantitative calculation of wire harness layout deviation, the matching weighted factor can be quickly retrieved from this mapping group to ensure the objectivity and reliability of the quantitative results.

[0044] In this embodiment, by statistically quantifying the crossover situation of UAV harnesses, the spatial distribution characteristics and electromagnetic risk superposition state of harness crossovers are comprehensively captured. This allows for the precise location of key harnesses with dense crossovers and high electromagnetic risks, avoiding risk omissions caused by single-dimensional assessments. Harness paths in high-risk areas can be optimized in a targeted manner, reducing the risk superposition of magnetic and electric field coupling caused by excessive harness crossovers. This provides data support for the electromagnetic compatibility and spatial rationality of UAV harness layout, and reduces the hidden danger of crossover interference to core signals.

[0045] Preferably, the specific process for adjusting the harness layout is as follows: Drone harness classification: When the harness layout deviation quantification index exceeds the preset first-level harness layout deviation threshold, the corresponding drone harness is classified as a first-level functional harness, and based on A... The algorithm generates the first optimal path set corresponding to the first-level functional harness and then deploys the first-priority harness. The preset first-level harness layout deviation threshold is pre-set by a pre-defined team. Option A is selected. The algorithm prioritizes the deployment of first-priority harnesses, facilitating rapid location of the optimal path within the compact equipment compartment of the UAV, ensuring the stability of signal transmission for the core harnesses. When the harness layout deviation quantification index is no greater than a preset first-level harness layout deviation threshold and no less than a preset second-level harness layout deviation threshold, the corresponding UAV harness is identified as a second-level functional harness. Based on the Dijkstra algorithm, a second set of suitable paths is generated for the second-level functional harness before second-priority harness deployment. The preset second-level harness layout deviation threshold is pre-set by designated personnel. Choosing the Dijkstra algorithm for second-priority harness deployment helps generate globally optimal paths for the second-level functional harnesses after the first-level harness layout is completed, reducing overlap with the first-level functional harness area and high-frequency electromagnetic interference, ensuring signal transmission stability of the core harnesses. To ensure the transmission reliability of the secondary functional harnesses, when the harness layout deviation quantification index is less than the preset secondary harness layout deviation threshold, the corresponding UAV harness is identified as a tertiary functional harness. Based on a greedy algorithm, a third flexible path set corresponding to the tertiary functional harness is generated, and then the third priority harness is deployed. Choosing the greedy algorithm for the third priority harness deployment helps to quickly adapt to the remaining space after the deployment of the primary and secondary functional harnesses, reduce computing power consumption through local optimal selection, improve the overall space utilization of the UAV equipment compartment, and not interfere with the primary and secondary functional harnesses. After the harness layout adjustment is completed, the harness layout deviation quantification index and the total number of harness layout deviations are reacquired. If the total number of harness layout deviations is still greater than the preset harness layout deviation threshold, a harness layout adjustment failure alarm is sent; otherwise, UAV signal fluctuation analysis is performed.

[0046] In this embodiment, by adjusting the harness layout, the UAV harness is divided into three levels of harnesses according to the harness layout deviation quantification index and matched with a dedicated algorithm, ensuring that the first-level functional harness passes A. The algorithm obtains the optimal low-interference path, ensuring the signal foundation for core functions such as UAV flight control and navigation. It also enables secondary functional harnesses to achieve stable interference avoidance with the help of Dijkstra's algorithm, supporting the reliability of mission data transmission. The tertiary functional harnesses flexibly fill the space through a greedy algorithm, improving the overall layout efficiency of the UAV equipment compartment. The hierarchical deployment mode avoids disorderly competition between harnesses of different priorities in a limited space, reduces the superposition of electromagnetic coupling risks caused by layout conflicts, maximizes space utilization while ensuring low interference of core signals, and effectively reduces the total number of harness layout deviations, providing a low-interference and high-compatibility foundation for subsequent signal fluctuation monitoring.

[0047] Preferably, as an embodiment of the first aspect, the UAV signal fluctuation analysis is used to evaluate the signal transmission stability of the UAV harness, promptly identify signal anomalies caused by factors such as electromagnetic interference and poor harness contact, and provide assurance for the signal reliability of UAV mission execution. The specific process is as follows: An amplitude fluctuation coefficient is obtained to evaluate the amplitude fluctuation of the DC voltage signal of the UAV harness; the amplitude fluctuation coefficient is represented by the ratio of the standard deviation of the DC voltage signal amplitude within a preset sampling period to a preset amplitude threshold, and is used to evaluate the amplitude stability of the UAV harness. The standard deviation of the DC voltage signal amplitude is calculated using a preset sampling period... Within the system, the sum of the squares of the differences between the DC voltage signal amplitude monitored by the DC voltage sensor at each sampling point and the preset amplitude threshold is divided by the total number of sampling points monitored by the DC voltage signal acquisition module, and the result is expressed as the square root. The preset amplitude threshold is represented by the average value of the DC voltage signal amplitude over a historical time period. The preset sampling period represents the time period for signal fluctuation analysis. The system determines whether the amplitude fluctuation coefficient is less than the preset amplitude fluctuation threshold. If it is, the signal fluctuation is considered normal and monitoring continues. Otherwise, an abnormal signal fluctuation alarm is sent. The preset amplitude fluctuation threshold is represented by the average value of the amplitude fluctuation coefficient over a historical time period.

[0048] As an embodiment of the first aspect, in this embodiment, by analyzing the signal fluctuation of the UAV, it is helpful to build a real-time monitoring mechanism for UAV harness signals with DC voltage signal amplitude fluctuation quantitative analysis as the core. It can accurately capture the subtle fluctuations of the signal amplitude within the preset sampling period, and investigate potential hidden dangers such as electromagnetic interference and poor harness contact from a technical perspective. It provides dynamic protection for the continuous and stable transmission of the UAV core harness, improves the objectivity and accuracy of the UAV harness signal stability assessment, and realizes the timely identification and early warning closed loop of UAV harness signal anomalies.

[0049] Preferably, as an embodiment of the second aspect, the specific process of analyzing UAV signal fluctuations is as follows: When the UAV is in a strong electromagnetic environment and the detected electromagnetic radiation intensity exceeds a preset radiation threshold, a UAV signal fluctuation index is obtained to comprehensively evaluate the stability and interference level of the UAV harness signal. The electromagnetic radiation intensity is monitored by an electromagnetic radiation detector, and the preset radiation threshold is set in advance by a preset person. The UAV signal fluctuation index is represented by the result of weighted coupling processing of interference fluctuation characteristic parameters and their influence values. The interference fluctuation characteristic parameters include the signal amplitude variation coefficient for characterizing signal amplitude stability, the phase jitter normalized value for characterizing signal phase synchronization, and the autocorrelation coefficient attenuation value for characterizing signal fluctuation persistence. The interference fluctuation characteristic parameter influence values ​​include the signal amplitude variation coefficient influence value for reflecting the influence of the signal amplitude variation coefficient on the UAV signal fluctuation index, the phase jitter normalized influence value for reflecting the influence of the phase jitter normalized value on the UAV signal fluctuation index, and the autocorrelation coefficient attenuation influence value for reflecting the influence of the autocorrelation coefficient attenuation value on the UAV signal fluctuation index.

[0050] Specifically, the formula for the coefficient of variation of signal amplitude is as follows:

[0051]

[0052] Among them, V A σ represents the coefficient of variation of the signal amplitude. A The standard deviation of the signal amplitude is represented by A0, which represents the preset signal amplitude. The standard deviation of the signal amplitude is calculated based on the standard deviation formula by continuously collecting frequency signal amplitude data of the UAV harness within the preset sampling period. It is used to quantify the degree of discrete fluctuation of the signal amplitude. The preset signal amplitude is represented by the average value of the standard deviation of the signal amplitude over a historical period.

[0053] Specifically, the formula for the phase jitter normalization value is as follows:

[0054]

[0055] Among them, V B σ represents the normalized value of phase jitter. B B0 represents the preset maximum phase jitter value. The phase jitter standard deviation is calculated based on the standard deviation formula by collecting phase data of the UAV harness within a preset sampling period. It is used to quantify the dispersion of phase jitter. The preset maximum phase jitter value is represented by the average value of the phase jitter peak values ​​over a historical time period.

[0056] Specifically, the formula for the autocorrelation coefficient decay value is as follows:

[0057]

[0058] Among them, V C ρ represents the autocorrelation coefficient decay value. T This represents the autocorrelation coefficient, which reflects the persistence of signal fluctuations.

[0059] Specifically, the formula for the autocorrelation coefficient is as follows:

[0060] ;

[0061] Where, ρ T x represents the autocorrelation coefficient. i This represents the i-th current signal amplitude data point. The signal amplitude sequence average value is represented by T, where T represents the time delay and n represents the number of sampling points. The autocorrelation coefficient is used to reflect the correlation of signal amplitude fluctuations in the time dimension within the preset sampling period, that is, the similarity of the amplitude fluctuation trend between the current moment and the moment after the delay T, thereby judging the persistence and regularity of signal fluctuations. The i-th signal amplitude data point is represented by the i-th discretized data point obtained by continuously collecting the current signal amplitude of the first-level functional harness at fixed time intervals by the UAV onboard signal acquisition module within the preset sampling period. The signal amplitude sequence average value is represented by the result of the arithmetic mean of all current signal amplitude data points collected within the preset sampling period. The time delay is preset by the personnel to reflect the time interval between two sampling moments.

[0062] Specifically, the formula for the drone signal fluctuation index is as follows:

[0063]

[0064] Wherein, SSFI represents the drone signal fluctuation index, W A W represents the influence value of the signal amplitude variation coefficient. B W represents the normalized effect value of phase jitter. C This represents the decay effect of the autocorrelation coefficient, where W A W B and W C All settings are pre-programmed by designated personnel.

[0065] If the signal fluctuation index of the drone is greater than the preset signal fluctuation threshold, an abnormal signal fluctuation alarm is sent; otherwise, the signal fluctuation is determined to be normal and monitoring continues. The preset signal fluctuation threshold is represented by the average value of the drone signal fluctuation index over a historical time period.

[0066] As an embodiment of the second aspect, in this embodiment, the UAV, under strong electromagnetic environment, uses the radiation intensity monitored in real time by the electromagnetic radiation detector as the trigger condition, and only initiates deep analysis when the intensity exceeds a preset threshold. This reduces redundant calculations in non-electromagnetic interference scenarios, adapts to the dynamic monitoring needs under strong electromagnetic environment, uses three types of interference fluctuation characteristic parameters to comprehensively capture abnormal states of the signal in different dimensions such as amplitude, phase, and fluctuation patterns, and generates a UAV signal fluctuation index that can comprehensively reflect the overall interference level of the signal under strong electromagnetic environment. This makes the evaluation results more consistent with the actual situation of signal interference under strong electromagnetic environment, improves the comprehensiveness and accuracy of UAV harness signal stability evaluation under strong electromagnetic environment, and effectively reduces problems such as UAV mission data distortion caused by strong electromagnetic interference.

[0067] Figure 4 shows a schematic diagram of a UAV harness layout system provided in an embodiment of this application. This UAV harness layout system, which applies a UAV harness layout method, is characterized by including: an electromagnetic coupling interference monitoring module, a UAV harness crossing situation monitoring module, and a signal fluctuation monitoring module. The electromagnetic coupling interference monitoring module performs electromagnetic coupling interference assessment of the UAV harness during the harness layout process, and determines whether magnetic field interference suppression and electric field interference suppression are needed based on the acquired electromagnetic coupling interference assessment results. The UAV harness crossing situation monitoring module performs UAV signal fluctuation analysis if the UAV harness electromagnetic coupling interference assessment is qualified; otherwise, it performs statistical quantification of the UAV harness crossing situation to accurately quantify the harness crossing density and the degree of electromagnetic risk superposition, and determines whether harness layout adjustment is needed based on the acquired statistical quantification results. The signal fluctuation monitoring module performs UAV signal fluctuation analysis to evaluate the harness signal stability and interference impact after the UAV harness crossing situation statistical quantification is completed, and determines whether a signal fluctuation anomaly alarm needs to be sent based on the acquired UAV signal fluctuation analysis results.

[0068] This application provides a drone wiring harness layout medium, which stores program code that can be called by a processor to execute any of the methods in a drone wiring harness layout method.

[0069] In this embodiment, an electromagnetic coupling interference monitoring module, a UAV harness crossing monitoring module, and a signal fluctuation monitoring module are progressively linked and work in synergy to construct a full-process dynamic monitoring system for UAV harness electromagnetic interference prevention and signal reliability assurance. The electromagnetic coupling interference monitoring module, as the source control link, assesses the risk of magnetic and electric field coupling between harnesses and takes targeted suppression measures, providing a harness layout foundation with low initial interference for subsequent modules. Its assessment results directly determine the working direction of the UAV harness crossing monitoring module. The UAV harness crossing monitoring module, based on the previous coupling assessment results, accurately quantifies the crossing density and the degree of electromagnetic risk superposition and optimizes the layout, thereby reducing electromagnetic interference. The coupling assessment addresses the crossover risks in scenarios where the coupling is not up to standard, while also providing a low-deviation, high-electromagnetic-compatibility harness layout environment for the signal fluctuation monitoring module. If the layout still fails to meet the standards after adjustment, a timely warning is issued to prevent the risk from spreading. As the terminal monitoring link, the signal fluctuation monitoring module connects with the layout optimization results of the UAV harness crossover monitoring module. It achieves anomaly warning by assessing signal stability. The three modules support each other and progress in a layered manner, improving the electromagnetic compatibility of the UAV harness layout and the reliability of signal transmission. This solves problems such as command delay, navigation drift, and mission data distortion caused by source coupling interference, overlapping risks of crossover in the middle, and lack of warning for abnormal signals at the end. It provides comprehensive technical support for the stable execution of UAV flight missions.

[0070] In summary, by conducting an electromagnetic coupling interference assessment of UAV wiring harnesses, and based on the obtained assessment results, it is determined whether magnetic field interference suppression and electric field interference suppression are necessary. This helps to reduce the electromagnetic coupling interference of low-frequency high-current wiring harnesses and high-frequency high-voltage wiring harnesses on core signal lines within the UAV equipment cabin from the source, laying the foundation for stable transmission of core signals. If the UAV wiring harness electromagnetic coupling interference assessment is satisfactory, then UAV signal fluctuation analysis is conducted; otherwise, statistical quantification of UAV wiring harness crossing conditions is performed to accurately quantify the density of wiring harness crossings and the degree of electromagnetic risk superposition. Based on the obtained statistical quantification results of UAV wiring harness crossing conditions, it is determined whether magnetic field interference suppression and electric field interference suppression are necessary. Adjusting the wiring harness layout helps reduce the superposition of electromagnetic risks caused by excessive wiring harness crossing, improves the electromagnetic compatibility and spatial rationality of the UAV wiring harness layout, and after the statistical quantification of UAV wiring harness crossing, conduct UAV signal fluctuation analysis to assess the stability of wiring harness signals and the degree of interference. Based on the obtained UAV signal fluctuation analysis results, determine whether to send a signal fluctuation anomaly alarm. This helps to promptly identify signal amplitude anomalies caused by residual electromagnetic interference, poor wiring harness contact, and other factors, reduce the impact of signal fluctuations on core functions such as autonomous flight and precise hovering of UAVs, and provide signal reliability assurance for the safe and stable execution of UAV missions.

[0071] The following points need to be explained:

[0072] (1) The accompanying drawings of the embodiments of the present invention only involve the structures involved in the embodiments of the present invention. Other structures can refer to the general design.

[0073] (2) For clarity, the thickness of layers or regions is enlarged or reduced in the drawings used to describe embodiments of the invention, i.e., these drawings are not drawn to scale. It is understood that when an element such as a layer, film, region or substrate is referred to as being “above” or “below” another element, the element may be “directly” located “above” or “below” the other element or there may be intermediate elements.

[0074] (3) Where there is no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other to obtain new embodiments.

[0075] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for arranging wiring harnesses for unmanned aerial vehicles (UAVs), characterized in that, The method includes: during the UAV wiring harness layout process, performing an electromagnetic coupling interference assessment of the UAV wiring harness; based on the obtained assessment results, determining whether magnetic field interference suppression and electric field interference suppression are necessary; the magnetic field interference suppression is used to weaken the mutual inductive coupling between the low-frequency high-current wiring harness and the core control signal line by optimizing the truncated parallel segments and turning angles in the UAV wiring harness layout; the electric field interference suppression is used to reduce the capacitive coupling between the high-frequency high-voltage wiring harness and the weak signal line by adjusting the safety distance in the UAV wiring harness layout; if the UAV wiring harness electromagnetic coupling interference assessment is qualified, then the UAV signal... The analysis of signal fluctuations is performed. Conversely, statistical quantification of UAV harness crossing density and electromagnetic risk superposition is conducted to accurately quantify the density of harness crossings and the degree of electromagnetic risk superposition. Based on the obtained statistical quantification results of UAV harness crossing, it is determined whether harness layout adjustment is necessary. The harness layout adjustment is used to optimize harness paths according to interference priority, thereby improving the electromagnetic compatibility and spatial rationality of the harness layout. After the statistical quantification of UAV harness crossing is completed, UAV signal fluctuation analysis is performed to evaluate the stability of harness signals and the degree of interference impact. Based on the obtained UAV signal fluctuation analysis results, it is determined whether to send a signal fluctuation anomaly alarm.

2. The method for arranging a UAV wiring harness according to claim 1, characterized in that, The electromagnetic coupling interference assessment of the UAV wiring harness is used to evaluate the electromagnetic coupling risks generated during the layout of different functional wiring harnesses in the UAV equipment compartment. The specific process is as follows: All wiring harnesses in the UAV equipment compartment are numbered to obtain a unique ID number corresponding to each wiring harness and generate a wiring harness pair matrix containing wiring harness pairs; the signal frequency corresponding to the interference source wiring harness in the wiring harness pair matrix is ​​monitored. When the corresponding signal frequency is less than a preset signal frequency, magnetic field coupling interference analysis is performed; otherwise, electric field coupling interference analysis is performed. The specific process of the magnetic field coupling interference analysis is as follows: The current intensity, signal frequency, and wiring harness pair spacing value of the interference source wiring harness are input into a preset mutual inductance coupling model to calculate the coupling strength, and the corresponding mutual inductance coefficient is output. The system detects interference voltage and performs magnetic field coupling interference judgment to identify the risk of magnetic field coupling caused by low-frequency high-current harnesses and ensure the stability of core control signal transmission for flight control and navigation. If the magnetic field coupling interference judgment is qualified, the system analyzes the UAV signal fluctuation; otherwise, it marks the number of UAV interference source harnesses with magnetic field coupling risk using harness pair magnetic field interference marking. The harness pair magnetic field interference marking involves incrementing the magnetic field mark counter by 1 and storing the corresponding interference source harness number sequentially in a preset magnetic field interference database. Simultaneously, it checks whether the magnetic field mark counter value is greater than a preset maximum magnetic field interference harness pair threshold. If so, magnetic field interference suppression is implemented, and the corresponding magnetic field mark counter value is reset to its initial value. Conversely, the evaluation of electromagnetic coupling interference of the UAV harness continues. The preset mutual inductance coupling model is used to quantify the magnetic field coupling effect between two harnesses in low-frequency scenarios. The mutual inductance coefficient is used to reflect the tightness of the magnetic field coupling between the two harnesses, and the induced interference voltage is used to reflect the interference intensity of the interference source harness to the interfered harness. The specific process of the magnetic field coupling interference judgment is as follows: determine whether the mutual inductance coefficient is less than the preset minimum threshold of mutual inductance coefficient and whether the induced interference voltage is less than the preset minimum threshold of induced interference voltage. If so, the magnetic field coupling interference judgment is qualified; otherwise, the magnetic field coupling interference judgment is unqualified. The specific process of the electric field coupling interference analysis is as follows: input the interference source harness voltage, signal frequency, and harness pair spacing value into the preset... The coupling strength is calculated in the capacitive coupling model, and the coupling capacitance and noise voltage of the corresponding wire harness pair are output. An electric field coupling interference judgment is performed to identify the risk of electric field coupling caused by the high-frequency, high-voltage wire harness. If the electric field coupling interference judgment is qualified, the UAV signal fluctuation is analyzed; otherwise, a wire harness pair electric field interference mark is used to record the number of times the electric field coupling interference judgment of the corresponding interference source wire harness fails. The wire harness pair electric field interference mark indicates that the electric field mark counter value of the corresponding interference source wire harness is incremented by 1, and it is determined whether the electric field mark counter value is greater than the preset maximum electric field interference threshold. If it is, electric field interference suppression is implemented, and the corresponding electric field mark counter value is reset to the initial value; otherwise, the electric field coupling interference analysis continues.The preset capacitive coupling model is used to quantify the electric field coupling effect between two wire bundles in high-frequency scenarios. The coupling capacitance reflects the strength of the electric field coupling between the two wire bundles, and the noise voltage reflects the amplitude of the signal influence of the interfering source wire bundle on the interfering wire bundle. The specific process of electric field coupling interference determination is as follows: determine whether the coupling capacitance is less than the preset minimum coupling capacitance threshold and whether the noise voltage is less than the preset minimum noise voltage threshold. If so, the electric field coupling interference determination is qualified; otherwise, it is determined that the electric field coupling interference determination is unqualified.

3. The UAV wiring harness layout method according to claim 2, characterized in that, The specific process of the magnetic field interference suppression is as follows: The interference source bundle numbers are retrieved sequentially from a preset magnetic field interference database, and the bundle pairs corresponding to these interference source bundle numbers are subjected to magnetic field bundle pair interference suppression. The specific process of the magnetic field bundle pair interference suppression is as follows: Optimization parameters for truncated parallel segments are obtained, including the maximum parallel length of a single segment, the minimum turning angle, the safety distance, and the density of fixed points. Based on the optimization parameters for truncated parallel segments, turning node planning and path decomposition are performed to obtain the bundle segment path planning results, including the coordinates of the bundle turning nodes, the turning angle, and the coordinates of the start and end points of each segment. Obtain the complete set of routing coordinates for each segment after planning the turning nodes and splitting the path, and adjust the harness segmentation based on the complete set of routing coordinates. The magnetic field coupling interference determination is re-performed. If the magnetic field coupling interference determination is qualified, the UAV signal fluctuation is analyzed. Otherwise, the UAV harness crossing situation is statistically quantified. After the current magnetic field harness pair interference suppression ends, the harness pair numbers are retrieved from the preset magnetic field interference database in sequence. If the preset magnetic field interference database is not empty, magnetic field interference suppression is adopted. Otherwise, the preset magnetic field interference database is cleared, and the current round of magnetic field interference suppression ends.

4. The UAV wiring harness layout method according to claim 2, characterized in that, The specific process of electric field interference suppression is as follows: the coupling capacitor and noise voltage input bundle amplification distance coefficient mapping set is queried to obtain the target amplification distance coefficient; the adjustment amplitude corresponding to the target amplification distance coefficient is used as the adjustment step size, and the actual spacing between the two bundles is adjusted step by step in the direction of increasing spacing of the bundle pair, and the adjusted spacing increment is superimposed on the current actual spacing of the bundle pair; The coupling capacitance and noise voltage are continuously monitored and electric field coupling interference is determined. If the electric field coupling interference determination is qualified, the UAV signal fluctuation is analyzed. Otherwise, electric field interference suppression is continued. When the number of electric field interference suppression executions exceeds the preset maximum execution threshold, if the electric field coupling interference determination is unqualified, the UAV harness crossing situation is statistically quantified.

5. The UAV wiring harness layout method according to claim 4, characterized in that, The specific process for statistical quantification of UAV harness crossing is as follows: Obtain harness layout deviation quantification data items to assess the severity of UAV harness layout crossing; these data items include: a crosspoint contribution to quantify the frequency of a single harness crossing, reflecting the density of the harness's crossing distribution in the overall layout; an overlap contribution to quantify the actual length ratio of a single harness crossing overlap, reflecting the scale of the effective overlap area formed by the harness and other harnesses; a mutual inductance contribution to quantify the risk of magnetic field coupling caused by a single harness crossing with other harnesses, relating to the impact of mutual inductance coefficients on core signal transmission interference; and a coupling capacitance contribution to quantify the risk of electric field coupling caused by a single harness crossing with other harnesses, relating to the impact of coupling capacitance on weak signal noise superposition; the crosspoint contribution is represented by the ratio of the number of single harness crosspoints to the total number of harness crosspoints in the UAV equipment compartment; the overlap contribution is represented by the ratio of the length of a single harness crossing overlap to the total length of harness crossing overlap; and the mutual inductance contribution is represented by the total value of the mutual inductance coefficient of a single harness. The result is represented by the proportion of the mutual inductance coefficient statistical value; the contribution of the coupling capacitor is represented by the proportion of the total value of the coupling capacitor of a single harness to the statistical value of the coupling capacitor; the result of weighted coupling processing of the harness local deviation data item and the corresponding harness local deviation weight parameter is used as the harness layout deviation quantitative index to characterize the degree of comprehensive influence of a single harness on the global layout deviation; the harness local deviation weight parameter includes the cross-point contribution weight factor to reflect the influence of the cross-point contribution on the harness layout deviation quantitative index, the overlap contribution weight factor to reflect the influence of the overlap contribution on the harness layout deviation quantitative index, the mutual inductance contribution weight factor to reflect the influence of the mutual inductance contribution on the harness layout deviation quantitative index, and the coupling capacitor contribution weight factor to reflect the influence of the coupling capacitor contribution on the harness layout deviation quantitative index; it is determined whether the total number of harness layout deviations is greater than the preset harness layout deviation threshold. If so, harness layout adjustment is taken to optimize the harness path planning in the UAV equipment cabin to ensure the stability of core signal transmission; otherwise, UAV signal fluctuation analysis is performed.

6. The UAV wiring harness layout method according to claim 5, characterized in that, The specific process of the harness layout adjustment is as follows: When the harness layout deviation quantification index is greater than the preset first-level harness layout deviation threshold, the corresponding UAV harness is determined as a first-level functional harness, and after generating the first optimal path set corresponding to the first-level functional harness, the first priority harness is deployed. When the quantitative index of the wiring harness layout deviation is not greater than the preset first-level wiring harness layout deviation threshold and not less than the preset second-level wiring harness layout deviation threshold, the corresponding UAV wiring harness is determined to be a second-level functional wiring harness, and after generating the second adaptation path set corresponding to the second-level functional wiring harness, the second priority wiring harness is deployed. When the harness layout deviation quantification index is less than the preset secondary harness layout deviation threshold, the corresponding UAV harness is determined to be a tertiary functional harness, and a third flexible path set corresponding to the tertiary functional harness is generated before the third priority harness is deployed. After the harness layout adjustment is completed, the harness layout deviation quantification index and the total number of harness layout deviations are reacquired. If the total number of harness layout deviations is still greater than the preset harness layout deviation threshold, a harness layout adjustment failure alarm is sent; otherwise, UAV signal fluctuation analysis is performed.

7. A method for arranging wiring harnesses for unmanned aerial vehicles according to claim 6, characterized in that, The analysis of drone signal fluctuations is used to evaluate the signal transmission stability of the drone harness. The specific process is as follows: obtain the amplitude fluctuation coefficient to evaluate the amplitude fluctuation of the DC voltage signal of the drone harness; the amplitude fluctuation coefficient is used to evaluate the amplitude stability of the drone harness. Determine whether the amplitude fluctuation coefficient is less than the preset amplitude fluctuation threshold. If it is, the signal fluctuation is considered normal; otherwise, an alarm for abnormal signal fluctuation is sent.

8. A method for arranging wiring harnesses for unmanned aerial vehicles according to claim 6, characterized in that, The specific process of analyzing the UAV signal fluctuation is as follows: When the UAV is in a strong electromagnetic environment and the electromagnetic radiation intensity exceeds the preset radiation threshold, the UAV signal fluctuation index is obtained to comprehensively evaluate the stability and interference level of the UAV harness signal. The UAV signal fluctuation index is represented by the result of weighted coupling processing of interference fluctuation characteristic parameters and interference fluctuation characteristic parameter influence values. The interference fluctuation characteristic parameters include the signal amplitude variation coefficient, which characterizes the signal amplitude stability; the phase jitter normalized value, which characterizes the signal phase synchronization; and the autocorrelation coefficient decay value, which characterizes the persistence of signal fluctuations. The interference fluctuation characteristic parameter impact values ​​include the signal amplitude variation coefficient impact value, which reflects the influence of the signal amplitude variation coefficient on the UAV signal fluctuation index; the phase jitter normalization impact value, which reflects the influence of the phase jitter normalization value on the UAV signal fluctuation index; and the autocorrelation coefficient decay impact value, which reflects the influence of the autocorrelation coefficient decay value on the UAV signal fluctuation index. The system determines whether the UAV signal fluctuation index is greater than a preset signal fluctuation threshold. If so, an abnormal signal fluctuation alarm is sent; otherwise, the signal fluctuation is determined to be normal, and monitoring continues.

9. A UAV wiring harness layout system, employing a UAV wiring harness layout method as described in any one of claims 1-8, characterized in that, include: The system includes an electromagnetic coupling interference monitoring module, a UAV harness crossing monitoring module, and a signal fluctuation monitoring module. The electromagnetic coupling interference monitoring module performs an electromagnetic coupling interference assessment of the UAV harness during the harness layout process, and determines whether magnetic field interference suppression and electric field interference suppression are needed based on the assessment results. The UAV harness crossing monitoring module analyzes UAV signal fluctuations if the electromagnetic coupling interference assessment is satisfactory; otherwise, it performs statistical quantification of the harness crossing density and the degree of electromagnetic risk superposition to accurately quantify the crossover density and the degree of electromagnetic risk superposition. Based on the statistical quantification results, it determines whether harness layout adjustments are needed. The signal fluctuation monitoring module analyzes UAV signal fluctuations after the statistical quantification of the harness crossing, assessing the signal stability and interference impact. Based on the analysis results, it determines whether a signal fluctuation anomaly alarm needs to be sent.

10. A computer-readable storage medium for a UAV wiring harness layout, characterized in that, The aforementioned drone harness layout is stored in a computer-readable storage medium containing program code that can be invoked by a processor to execute the method as described in any one of claims 1-8.

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