Aviation obstruction light malfunction early warning method, device and storage medium

Abstract

This invention relates to the field of aviation obstruction light technology, and more particularly to an aviation obstruction light fault early warning method, device, and storage medium. The method includes: determining the salt spray erosion intensity based on the salt spray concentration at the top, middle, and bottom of the tower; determining vibration anomaly characteristics based on triaxial vibration acceleration; determining obstruction light seal degradation characteristics based on the obstruction light DC bus voltage, the power factor of the obstruction light drive circuit, and the humidity of the obstruction light sealing cavity; determining a comprehensive degradation index based on the obstruction light electrical characteristics and the obstruction light seal degradation characteristics; adjusting the determination process of the comprehensive degradation index based on the vibration anomaly characteristics; determining the obstruction light degradation state based on the adjusted comprehensive degradation index and issuing an obstruction light degradation early warning to the user; determining fault risk factors and issuing a fault maintenance alarm to the user; and simultaneously adjusting the overcurrent protection threshold for the next fault detection cycle based on the fault risk factors. This invention significantly improves the accuracy of fault early warning and operational efficiency.

Description

Technical Field

[0001] This invention relates to the field of aviation obstruction light technology, and in particular to an aviation obstruction light malfunction early warning method, device and storage medium. Background Technology

[0002] Traditionally, the maintenance of aviation obstruction lights at offshore wind farms has relied primarily on periodic manual inspections, simple timed replacements, or reactive repairs after malfunctions. This approach has significant drawbacks: manual inspections are costly, inefficient, and limited by adverse sea conditions; the timed replacement strategy fails to consider the actual condition of the equipment, resulting in resource waste; and post-malfunction repairs can lead to prolonged light outages, jeopardizing aviation safety, and are extremely difficult and risky.

[0003] Existing remote monitoring solutions are mostly limited to a single parameter and cannot fully reflect the equipment deterioration process caused by the coupling effect of multiple factors such as complex marine environment and internal electrical aging and sealing failure. Therefore, they are difficult to achieve effective early fault warning and accurate maintenance decision support. Summary of the Invention

[0004] The purpose of this invention is to provide an aviation obstruction light malfunction early warning method, device, and storage medium to solve at least one of the problems existing in the prior art.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A method for early warning of aviation obstruction light malfunctions includes:

[0007] The intensity of salt spray erosion is determined based on the salt spray concentration at the top, middle, and bottom of the tower.

[0008] Vibration intensity and dominant vibration frequency are extracted based on triaxial vibration acceleration, and then the vibration frequency distribution characteristics are determined. Vibration anomaly characteristics are determined based on vibration intensity and vibration frequency distribution characteristics.

[0009] The electrical characteristics of the obstruction lamp are determined based on the DC bus voltage of the obstruction lamp and the power factor of the obstruction lamp drive circuit. The sealing degradation characteristics of the obstruction lamp are determined based on the humidity of the obstruction lamp sealing cavity. The comprehensive degradation index is determined based on the electrical characteristics and sealing degradation characteristics of the obstruction lamp.

[0010] The process of determining the comprehensive degradation index is adjusted based on the abnormal vibration characteristics. The degradation status of the obstruction lights is determined based on the adjusted comprehensive degradation index, and obstruction light degradation warnings are issued to users.

[0011] Based on the salt spray erosion intensity, abnormal vibration characteristics, and obstruction light deterioration warnings during the fault detection cycle, fault risk factors are determined, and fault maintenance alarms are issued to users. At the same time, the overcurrent protection threshold for the next fault detection cycle is adjusted according to the fault risk factors.

[0012] Furthermore, the average value μt of the salt spray concentration sequence at the top of the tower, the average value μm of the salt spray concentration sequence in the middle of the tower, and the average value μb of the salt spray concentration sequence at the bottom of the tower are calculated within the analysis period. At the same time, the 95th percentile Pt of the salt spray concentration sequence at the top of the tower, the 95th percentile Pm of the salt spray concentration sequence in the middle of the tower, and the 95th percentile Pb of the salt spray concentration sequence at the bottom of the tower are calculated within the analysis period.

[0013] The vertical gradient ratio GR of salt spray concentration is calculated based on μt and μb, where GR = (μt - μb) / H, and H is the tower height.

[0014] The salt spray erosion intensity SE is determined based on μt, Pt, and GR.

[0015] Furthermore, for the triaxial vibration acceleration time series (ax, ay, az) within the analysis period, its synthetic acceleration time series is calculated, and the root mean square value of the synthetic acceleration time series is calculated as the vibration intensity VI.

[0016] Perform a fast Fourier transform on the synthetic acceleration time series and calculate its power spectral density. Within a preset frequency range, find the frequency point with the largest power spectral density and record it as the dominant vibration frequency DVF of the analysis period. The preset frequency band is 1Hz-50Hz.

[0017] The proportion of energy in the power spectral density within the DVF±0.5Hz frequency band to the total energy of the preset frequency band is used as the vibration frequency distribution characteristic, denoted as VB;

[0018] Based on the vibration intensity VI and the vibration frequency distribution characteristics VB, the vibration anomaly characteristics ZU are determined, ZU=min(1,(VI / Vy+η×VB));

[0019] Where Vy is the preset vibration intensity threshold and η is the preset correction coefficient.

[0020] Furthermore, the average DC bus voltage Vd of the obstacle lamp at each sampling point within the analysis period is calculated;

[0021] Subtract Vd from the bus voltage at each sampling point within the analysis period to obtain the ripple voltage at that sampling point. Calculate the root mean square value of the ripple voltage within the analysis period, denoted as Vr.

[0022] The voltage ripple factor RF is determined based on Vd and Vr, where RF = Vr / Vd;

[0023] Compare RF with a preset voltage ripple threshold r0 to determine the first electrical characteristic D1: when RF is less than or equal to r0, determine D1 as 0; otherwise, determine D1 = ln[5×(RF-r0)+1] / ln6;

[0024] The second electrical characteristic D2 is determined based on the power factor PF during the analysis period, where D2 = (P0 - PF) / P0;

[0025] The electrical characteristic Dz of the obstruction light is determined by combining the first electrical characteristic D1 and the second electrical characteristic D2, where Dz = r1 × D1 + r2 × D2;

[0026] Where r1 is the first electrical weight, r2 is the second electrical weight, P0 is the preset power factor, and r1+r2=1.

[0027] Furthermore, the humidity s0 of the obstruction light sealing cavity is compared with the preset humidity s1 to determine the obstruction light sealing degradation characteristic LD. If s0 is less than or equal to the preset humidity s1, the obstruction light sealing degradation characteristic LD is determined to be 0. If s0 is greater than the preset humidity s1, the obstruction light sealing degradation characteristic LD is determined to be min(1,(s0-s1) / △s); where △s is the preset humidity difference.

[0028] The comprehensive deterioration index Lz is determined by combining the electrical characteristics Dz and the sealing deterioration characteristics LD of the obstacle light, where Lz = u1 × Dz + u2 × LD;

[0029] Where u1 is the electrical characteristic weight, u2 is the sealing degradation weight, and u1+u2=1.

[0030] Furthermore, the vibration anomaly characteristic ZU is compared with the preset anomaly coefficient z0. When ZU is greater than z0, the electrical characteristic weight is adjusted to 0.8×u1 and the sealing deterioration weight is adjusted to (1-0.8×u1) to adjust the determination process of the comprehensive deterioration index. Otherwise, the electrical characteristic weight and sealing deterioration weight are not adjusted.

[0031] The adjusted comprehensive degradation index is set to Lzt. If Lzt is less than or equal to the preset warning threshold, no warning will be issued to the user regarding the degradation of the obstruction lights; otherwise, a warning will be issued to the user regarding the degradation of the obstruction lights.

[0032] Furthermore, based on the salt spray erosion intensity, abnormal vibration characteristics, and obstruction light deterioration warnings during the fault detection cycle, fault risk factors are determined, and fault maintenance alarms are issued to users. At the same time, the overcurrent protection threshold for the next fault detection cycle is adjusted according to the fault risk factors.

[0033] Furthermore, the number of analysis cycles in which the salt spray erosion intensity SE is greater than the salt spray erosion intensity threshold sy within the fault detection cycle is counted and denoted as k1;

[0034] The number of analysis cycles in which the vibration anomaly characteristic ZU is greater than the preset anomaly coefficient z0 within the fault detection cycle is counted and denoted as k2;

[0035] The number of analysis cycles during which warnings of obstruction light deterioration are issued to users within the statistical fault monitoring cycle is denoted as k3;

[0036] Based on k1, k2 and k3, the risk factor Fv is determined. When the risk factor Fv is greater than the preset risk threshold Ff, a fault repair alarm is issued to the user; otherwise, no fault repair warning is issued to the user.

[0037] When the risk factor Fv is less than or equal to the preset risk threshold Ff, the overcurrent protection threshold Ibase for the next fault detection cycle is set to max(Ibmin,Ibase×(1-γ×(Fv-Ff))).

[0038] Where γ is the preset adjustment coefficient, Ibase is the overcurrent protection reference threshold, and Ibmin is the minimum protection threshold.

[0039] According to another aspect of this application, an aviation obstruction light malfunction early warning device is provided, comprising: an erosion analysis unit for determining the salt spray erosion intensity based on the salt spray concentration at the top, middle, and bottom of the tower;

[0040] The feature extraction unit is used to extract vibration intensity and dominant vibration frequency based on triaxial vibration acceleration, and then determine vibration frequency distribution characteristics, and determine vibration anomaly characteristics based on vibration intensity and vibration frequency distribution characteristics;

[0041] The degradation determination unit is used to determine the electrical characteristics of the obstruction lamp based on the DC bus voltage of the obstruction lamp and the power factor of the obstruction lamp drive circuit, determine the sealing degradation characteristics of the obstruction lamp based on the humidity of the obstruction lamp sealing cavity, and determine the comprehensive degradation index based on the electrical characteristics and sealing degradation characteristics of the obstruction lamp.

[0042] The early warning unit is used to adjust the process of determining the comprehensive degradation index based on the abnormal vibration characteristics, determine the degradation status of the obstruction lights based on the adjusted comprehensive degradation index, and provide the user with an early warning of obstruction light degradation.

[0043] The fault detection unit is used to determine the fault risk factors based on the salt spray erosion intensity, abnormal vibration characteristics, and obstruction light deterioration warnings during the fault detection cycle, and to issue a fault maintenance alarm to the user. At the same time, it adjusts the overcurrent protection threshold for the next fault detection cycle based on the fault risk factors.

[0044] According to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, wherein the computer program is used to control the electronic device on which the computer-readable storage medium is located to perform the aviation obstruction light malfunction warning method during runtime.

[0045] The beneficial effects of this invention are as follows: This solution provides an intelligent fault early warning and health management system for offshore wind power aviation obstruction lights. It constructs a complete technical chain from microscopic state perception to macroscopic risk prediction by deeply integrating multi-source heterogeneous data such as environmental salt spray, mechanical vibration, electrical parameters, and sealing status. The solution innovatively establishes a dynamic impact model of vibration environment on electrical degradation and realizes adaptive protection strategy adjustment based on long-term risk assessment. Its beneficial effects lie in its ability to significantly improve the early identification capability of potential faults, transforming the maintenance mode from periodic inspections and reactive repairs to precise predictive maintenance, thereby effectively reducing the rate of sudden failures, reducing unplanned downtime, extending equipment lifespan, and ultimately ensuring the safe and stable operation of offshore wind farms and navigation safety, demonstrating significant economic and safety value. Attached Figure Description

[0046] 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.

[0047] Figure 1 This is a flowchart illustrating the aviation obstruction light malfunction early warning method of this embodiment.

[0048] Figure 2 This is a flowchart illustrating the method for determining the overall degradation index in this embodiment.

[0049] Figure 3 This is a flowchart illustrating the fault detection method in this embodiment.

[0050] Figure 4 This is a schematic diagram of the structure of the aviation obstruction light malfunction early warning device in this embodiment. Detailed Implementation

[0051] To more clearly illustrate the present invention, the following description, in conjunction with preferred embodiments and accompanying drawings, further clarifies the invention. Similar components in the drawings are indicated by the same reference numerals. Those skilled in the art should understand that the specific description below is illustrative rather than restrictive and should not be construed as limiting the scope of protection of the present invention.

[0052] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0053] Specifically, this embodiment is applied to the aviation obstruction light fault warning at the top of the monopile wind turbine tower in an offshore wind farm.

[0054] Please see Figure 1 As shown, this is a flowchart illustrating the aviation obstruction light malfunction early warning method of this embodiment. Before the method is executed, the system synchronously collects data through multiple sensors and monitoring units deployed on the wind turbine tower and the obstruction light body, including:

[0055] Salt spray concentration data: Environmental salt spray concentration values ​​are collected once per minute by salt spray concentration sensors installed at three typical heights: the top of the tower (near the obstruction light), the middle (about 1 / 2 tower height), and the bottom (near sea level), forming a time series.

[0056] Vibration data: A triaxial accelerometer is installed at the mounting base of the obstruction light to collect instantaneous values ​​of vibration acceleration in the X, Y, and Z axes at a sampling frequency of 100Hz.

[0057] Electrical and status data: The instantaneous value of the DC bus voltage is read from the monitoring loop of the obstruction light drive controller at a frequency of once per second;

[0058] The real-time power factor is read from the metering unit of the obstruction light drive circuit once per second. The power factor is the ratio of active power to apparent power, which characterizes the actual utilization efficiency of electrical energy by the load in the AC power supply system.

[0059] A temperature and humidity sensor is installed inside the sealed cavity of the obstruction light to collect the humidity value inside the cavity once per minute;

[0060] In this embodiment, no specific limitation is made on the communication protocol and transmission method of the above data. Those skilled in the art can set it freely according to the site conditions. The method performs cyclic calculation and early warning with an analysis cycle of 0.5 hours and a fault detection cycle of 24 hours.

[0061] The method includes:

[0062] Step S1: Determine the salt spray erosion intensity based on the salt spray concentrations at the top, middle, and bottom of the tower.

[0063] Specifically, the average value μt of the salt spray concentration sequence at the top of the tower, the average value μm of the salt spray concentration sequence in the middle of the tower, and the average value μb of the salt spray concentration sequence at the bottom of the tower are calculated within the analysis period. At the same time, the 95th percentile Pt of the salt spray concentration sequence at the top of the tower, the 95th percentile Pm of the salt spray concentration sequence in the middle of the tower, and the 95th percentile Pb of the salt spray concentration sequence at the bottom of the tower are calculated within the analysis period.

[0064] The vertical gradient ratio GR of salt spray concentration is calculated based on μt and μb, where GR = (μt - μb) / H, and H is the tower height.

[0065] Determine the salt spray erosion intensity SE based on μt, Pt, and GR:

[0066] When μt is less than or equal to the first concentration threshold n1, the first corrosion factor is determined to be 0; otherwise, the first corrosion factor is determined to be min(1,(μt-n1) / n1).

[0067] If Pt is less than or equal to the second concentration threshold n2, the second corrosion factor is determined to be 0; otherwise, the second corrosion factor is determined to be min(1,(Pt-n2) / n2)).

[0068] The salt spray erosion intensity SE is determined based on the first corrosion factor, the second corrosion factor, and GR, where SE = w1 × first corrosion factor + w2 × second corrosion factor + w3 × tanh(GR / G0).

[0069] Where w1 is the first erosion weight, w2 is the second erosion weight, w3 is the gradient weight, w1+w2+w3=1, and G0 is the preset gradient ratio.

[0070] Specifically, in this embodiment, the first concentration threshold is 50 μg / m³, the second concentration threshold is 200 μg / m³, the first corrosion weight is 0.3, the second corrosion weight is 0.5, the gradient weight is 0.2, and the preset gradient ratio is 0.5 (μg / m³) / m.

[0071] Specifically, this step constructs a multi-dimensional environmental erosion assessment model by monitoring the salt spray concentration at different heights of the wind turbine tower. It not only considers the direct exposure concentration at the obstruction light installation location, but also accurately depicts the physical process of salt spray diffusion with increasing height by introducing the vertical gradient ratio, thus more scientifically reflecting the severity of the microenvironment in which the equipment is located.

[0072] Please continue reading. Figure 1 As shown, the aviation obstruction light malfunction early warning method further includes:

[0073] Step S2: Extract vibration intensity and dominant vibration frequency based on triaxial vibration acceleration, and then determine vibration frequency distribution characteristics. Based on vibration intensity and vibration frequency distribution characteristics, determine vibration anomaly characteristics.

[0074] Specifically, for the triaxial vibration acceleration time series (ax, ay, az) within the analysis period, its synthetic acceleration time series is calculated, and the root mean square value of the synthetic acceleration time series is calculated as the vibration intensity VI.

[0075] Perform a fast Fourier transform on the synthetic acceleration time series and calculate its power spectral density. Within a preset frequency range, find the frequency point with the largest power spectral density and record it as the dominant vibration frequency DVF of the analysis period. The preset frequency band is 1Hz-50Hz.

[0076] The proportion of energy in the power spectral density within the DVF±0.5Hz frequency band to the total energy of the preset frequency band is used as the vibration frequency distribution characteristic, denoted as VB;

[0077] Based on the vibration intensity VI and the vibration frequency distribution characteristics VB, the vibration anomaly characteristics ZU are determined, ZU=min(1,(VI / Vy+η×VB));

[0078] Where Vy is the preset vibration intensity threshold and η is the preset correction coefficient.

[0079] Specifically, in this embodiment, the preset vibration intensity threshold is 0.5 m / s², and the preset correction coefficient is 0.5.

[0080] Specifically, this step achieves multi-dimensional perception of the mechanical state by performing time-frequency domain joint analysis on the triaxial vibration signal of the equipment body. It can not only quantify the overall energy level of the vibration, but also identify the frequency distribution characteristics of the vibration energy, thereby effectively distinguishing between broadband vibration caused by normal wind load and abnormal vibration caused by component loosening, resonance or damage, where energy is concentrated in a specific frequency band.

[0081] Please continue reading. Figure 1 As shown, the aviation obstruction light malfunction early warning method further includes:

[0082] Step S3: Determine the electrical characteristics of the obstruction lamp based on the DC bus voltage of the obstruction lamp and the power factor of the obstruction lamp drive circuit; determine the sealing degradation characteristics of the obstruction lamp based on the humidity of the obstruction lamp sealing cavity; and determine the comprehensive degradation index based on the electrical characteristics and sealing degradation characteristics of the obstruction lamp.

[0083] Please see Figure 2 As shown, the method for determining the overall degradation index includes:

[0084] Step S31: Determine the electrical characteristics of the obstacle lamp based on the DC bus voltage of the obstacle lamp and the power factor of the obstacle lamp drive circuit.

[0085] Specifically, the average DC bus voltage Vd of the obstacle lamps at each sampling point is calculated and analyzed within the period.

[0086] The ripple voltage at each sampling point is obtained by subtracting Vd from the bus voltage at each sampling point within the analysis period. The root mean square value of the ripple voltage within the analysis period is calculated and denoted as Vr.

[0087] The voltage ripple factor RF is determined based on Vd and Vr, where RF = Vr / Vd;

[0088] Compare RF with a preset voltage ripple threshold r0 to determine the first electrical characteristic D1: when RF is less than or equal to r0, determine D1 as 0; otherwise, determine D1 = ln[5×(RF-r0)+1] / ln6;

[0089] The second electrical characteristic D2 is determined based on the power factor PF during the analysis period, where D2 = (P0 - PF) / P0;

[0090] The electrical characteristic Dz of the obstruction light is determined by combining the first electrical characteristic D1 and the second electrical characteristic D2, where Dz = r1 × D1 + r2 × D2;

[0091] Where r1 is the first electrical weight, r2 is the second electrical weight, P0 is the preset power factor, and r1+r2=1.

[0092] Specifically, in this embodiment, the voltage ripple threshold is 5%, the first electrical weight is 0.7, the first electrical weight is 0.3, and the preset power factor is 0.92.

[0093] Specifically, by simultaneously monitoring the steady-state level and ripple fluctuation of the DC bus voltage, potential problems such as the degradation of the power module's filtering performance and the increase in line contact resistance can be accurately diagnosed. Combined with power factor assessment, the operating efficiency and health status of the drive circuit can be further judged, realizing a comprehensive understanding of the core electrical system from power supply quality to energy conversion efficiency.

[0094] Please continue reading. Figure 2 As shown, the method for determining the overall degradation index further includes:

[0095] Step S32: Determine the deterioration characteristics of the barrier lamp seal based on the humidity of the barrier lamp sealing cavity, and determine the comprehensive deterioration index based on the electrical characteristics of the barrier lamp and the deterioration characteristics of the barrier lamp seal.

[0096] Specifically, the humidity s0 of the obstruction light sealing cavity is compared with the preset humidity s1 to determine the obstruction light sealing degradation characteristic LD. If s0 is less than or equal to the preset humidity s1, the obstruction light sealing degradation characteristic LD is determined to be 0. If s0 is greater than the preset humidity s1, the obstruction light sealing degradation characteristic LD is determined to be min(1,(s0-s1) / △s); where △s is the preset humidity difference.

[0097] The comprehensive deterioration index Lz is determined by combining the electrical characteristics Dz and the sealing deterioration characteristics LD of the obstacle light, where Lz = u1 × Dz + u2 × LD;

[0098] Where u1 is the electrical characteristic weight, u2 is the sealing degradation weight, and u1+u2=1.

[0099] Specifically, in this embodiment, the electrical characteristic weight is 0.65, the sealing degradation weight is 0.35, the humidity difference is 45% RH, and the preset humidity is 30% RH.

[0100] Specifically, by directly monitoring the humidity inside the sealed cavity, the ultimate indicator, the physical sealing integrity of the lamp can be directly and reliably determined. By weighting and integrating electrical characteristics with sealing degradation characteristics, the assessment results can reflect both the current functional performance decline and the risk of future sudden failures caused by sealing failure, thus achieving a comprehensive assessment of the health status of the equipment in a timely and forward-looking manner.

[0101] Please continue reading. Figure 1 As shown, the aviation obstruction light malfunction early warning method further includes:

[0102] Step S4 involves adjusting the determination process of the comprehensive degradation index based on the abnormal vibration characteristics, determining the degradation status of the obstruction lights based on the adjusted comprehensive degradation index, and issuing an obstruction light degradation warning to the user.

[0103] Specifically, the vibration anomaly characteristic ZU is compared with the preset anomaly coefficient z0. When ZU is greater than z0, the electrical characteristic weight is adjusted to 0.8×u1 and the sealing deterioration weight is adjusted to (1-0.8×u1) to adjust the determination process of the comprehensive deterioration index. Otherwise, the electrical characteristic weight and sealing deterioration weight are not adjusted.

[0104] The adjusted comprehensive degradation index is set to Lzt. If Lzt is less than or equal to the preset warning threshold, no warning will be issued to the user regarding the degradation of the obstruction lights; otherwise, a warning will be issued to the user regarding the degradation of the obstruction lights.

[0105] Specifically, in this embodiment, the preset anomaly coefficient is 0.7 and the preset early warning threshold is 0.75.

[0106] Specifically, a dynamic weight adjustment mechanism is introduced. When significant abnormal vibration is detected, the weight of electrical characteristics that are more sensitive to vibration is automatically increased in the comprehensive evaluation. This simulates the physical reality that abnormal vibration can accelerate the deterioration of electrical connections and cause instantaneous open circuits or short circuits. This makes the early warning model no longer static, but able to adaptively adjust according to the real-time mechanical stress environment of the equipment, thereby issuing more context-aware and accurate early warnings.

[0107] Please continue reading. Figure 1 As shown, the aviation obstruction light malfunction early warning method further includes:

[0108] Step S5: Determine the fault risk factors based on the salt spray erosion intensity, abnormal vibration characteristics, and obstruction light deterioration warning during the fault detection cycle, and issue a fault repair alarm to the user. At the same time, adjust the overcurrent protection threshold for the next fault detection cycle based on the fault risk factors.

[0109] Please see Figure 3 As shown, the fault detection method includes:

[0110] Step S51: Determine the fault risk factors based on the salt spray erosion intensity, abnormal vibration characteristics, and obstruction light deterioration warning during the fault detection cycle, and issue a fault repair alarm to the user.

[0111] Specifically, the number of analysis cycles in which the salt spray erosion intensity SE is greater than the salt spray erosion intensity threshold sy within the fault detection cycle is denoted as k1;

[0112] The number of analysis cycles in which the vibration anomaly characteristic ZU is greater than the preset anomaly coefficient z0 within the fault detection cycle is counted and denoted as k2;

[0113] The number of analysis cycles during which warnings of obstruction light deterioration are issued to users within the statistical fault monitoring cycle is denoted as k3;

[0114] The risk factor Fv is determined based on k1, k2 and k3, Fv=(d1×k1+d2×k2+d3×k3) / Kz, where d1, d2 and d3 are weighting coefficients, d1+d2+d3=1, and Kz is the total number of analysis cycles within the fault detection cycle;

[0115] When the risk factor Fv is greater than the preset risk threshold Ff, a fault repair alarm will be issued to the user; otherwise, no fault repair warning will be issued to the user.

[0116] Specifically, in this embodiment, the preset salt spray erosion intensity threshold is 0.65, the preset risk threshold is 0.55, d1 is 0.25, d2 is 0.35, and d3 is 0.4.

[0117] Specifically, by statistically analyzing and integrating various early warning events within a complete operation and maintenance cycle, a comprehensive fault risk factor is generated. This factor transforms discrete, short-term abnormal signals into continuous, long-term risk probabilities, providing operation and maintenance personnel with clear and quantitative decision-making basis for whether to arrange maintenance immediately. This effectively avoids interference from single false alarms and improves the scientific nature and efficiency of operation and maintenance decisions.

[0118] Please see Figure 3 As shown, the fault detection method further includes:

[0119] Step S52: Adjust the overcurrent protection threshold for the next fault detection cycle based on the fault risk factor.

[0120] Specifically, when the risk factor Fv is less than or equal to the preset risk threshold Ff, the overcurrent protection threshold Ibase for the next fault detection cycle is set to max(Ibmin,Ibase×(1-γ×(Fv-Ff))).

[0121] Where γ is the preset adjustment coefficient, Ibase is the overcurrent protection reference threshold, and Ibmin is the minimum protection threshold.

[0122] Specifically, in this embodiment, the preset adjustment coefficient is 0.15, the overcurrent protection reference threshold is 0.7×Ibase, where Ibase is 1.2 times the rated operating current of the obstacle light drive circuit; and Ibmin is 0.8 times the rated operating current.

[0123] Specifically, the risk assessment results are applied in reverse to the equipment control system. When the system determines that the risk of failure has increased, the overcurrent protection threshold is automatically lowered, making the protection device more likely to operate in the early stage of the failure. Although this may increase the number of occasional protection actions, it can greatly prevent the problem of corrosion, loosening and other issues from eventually evolving into serious electrical short circuits or fires. This reflects the advanced maintenance concept of moving from "post-event maintenance" to "pre-event prevention and protection".

[0124] Please see Figure 4 As shown, the aviation obstruction light malfunction early warning device includes:

[0125] The erosion analysis unit is used to determine the salt spray erosion intensity based on the salt spray concentration at the top, middle, and bottom of the tower.

[0126] The feature extraction unit is used to extract vibration intensity and dominant vibration frequency based on triaxial vibration acceleration, and then determine vibration frequency distribution characteristics, and determine vibration anomaly characteristics based on vibration intensity and vibration frequency distribution characteristics;

[0127] The degradation determination unit is used to determine the electrical characteristics of the obstruction lamp based on the DC bus voltage of the obstruction lamp and the power factor of the obstruction lamp drive circuit, determine the sealing degradation characteristics of the obstruction lamp based on the humidity of the obstruction lamp sealing cavity, and determine the comprehensive degradation index based on the electrical characteristics and sealing degradation characteristics of the obstruction lamp.

[0128] The early warning unit is used to adjust the process of determining the comprehensive degradation index based on the abnormal vibration characteristics, determine the degradation status of the obstruction lights based on the adjusted comprehensive degradation index, and provide the user with an early warning of obstruction light degradation.

[0129] The fault detection unit is used to determine the fault risk factors based on the salt spray erosion intensity, abnormal vibration characteristics, and obstruction light deterioration warnings during the fault detection cycle, and to issue a fault maintenance alarm to the user. At the same time, it adjusts the overcurrent protection threshold for the next fault detection cycle based on the fault risk factors.

[0130] The aviation obstruction light malfunction early warning device provided in this application embodiment can execute the aviation obstruction light malfunction early warning method provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects of the execution method.

[0131] This application also provides a computer-readable storage medium, which is a tangible physical storage medium that can store the aforementioned computer program and various types of data used in the program; the physical storage medium includes, but is not limited to, existing physical storage media or combinations thereof, such as random access memory, read-only memory, optical disk, and hard disk.

[0132] Those skilled in the art will understand that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technique for storing information (such as computer-readable programs, data structures, program modules, or other data). Furthermore, it is known to those skilled in the art that communication media typically contain computer-readable programs, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and can include any information delivery medium.

[0133] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. For those skilled in the art, other variations or modifications can be made based on the above description. It is impossible to exhaustively list all the implementation methods here. All obvious variations or modifications derived from the technical solutions of the present invention are still within the protection scope of the present invention.

Claims

1. A method for early warning of aviation obstruction light malfunctions, characterized in that, include: The intensity of salt spray erosion is determined based on the salt spray concentration at the top, middle, and bottom of the tower. Vibration intensity and dominant vibration frequency are extracted based on triaxial vibration acceleration, and then the vibration frequency distribution characteristics are determined. Vibration anomaly characteristics are determined based on vibration intensity and vibration frequency distribution characteristics. The electrical characteristics of the obstruction lamp are determined based on the DC bus voltage of the obstruction lamp and the power factor of the obstruction lamp drive circuit. The sealing degradation characteristics of the obstruction lamp are determined based on the humidity of the obstruction lamp sealing cavity. The comprehensive degradation index is determined based on the electrical characteristics and sealing degradation characteristics of the obstruction lamp. The process of determining the comprehensive degradation index is adjusted based on the abnormal vibration characteristics. The degradation status of the obstruction lights is determined based on the adjusted comprehensive degradation index, and obstruction light degradation warnings are issued to users. Based on the salt spray erosion intensity, abnormal vibration characteristics, and obstruction light deterioration warnings during the fault detection cycle, fault risk factors are determined, and fault maintenance alarms are issued to users. At the same time, the overcurrent protection threshold for the next fault detection cycle is adjusted according to the fault risk factors.

2. The aviation obstruction light malfunction early warning method according to claim 1, characterized in that, Calculate the average value μt of the salt spray concentration sequence at the top of the tower, the average value μm of the salt spray concentration sequence in the middle of the tower, and the average value μb of the salt spray concentration sequence at the bottom of the tower within the analysis period. At the same time, calculate the 95th percentile Pt of the salt spray concentration sequence at the top of the tower, the 95th percentile Pm of the salt spray concentration sequence in the middle of the tower, and the 95th percentile Pb of the salt spray concentration sequence at the bottom of the tower within the analysis period. The vertical gradient ratio GR of salt spray concentration is calculated based on μt and μb, where GR = (μt - μb) / H, and H is the tower height. The salt spray erosion intensity SE is determined based on μt, Pt, and GR.

3. The aviation obstruction light malfunction early warning method according to claim 2, characterized in that, For the triaxial vibration acceleration time series (ax, ay, az) within the analysis period, calculate its composite acceleration time series, and calculate the root mean square value of the composite acceleration time series as the vibration intensity VI; Perform a fast Fourier transform on the synthetic acceleration time series and calculate its power spectral density. Within a preset frequency range, find the frequency point with the largest power spectral density and record it as the dominant vibration frequency DVF of the analysis period. The preset frequency band is 1Hz-50Hz. The proportion of energy in the power spectral density within the DVF±0.5Hz frequency band to the total energy of the preset frequency band is used as the vibration frequency distribution characteristic, denoted as VB; Based on the vibration intensity VI and the vibration frequency distribution characteristics VB, the vibration anomaly characteristics ZU are determined, ZU=min(1,(VI / Vy+η×VB)); Where Vy is the preset vibration intensity threshold and η is the preset correction coefficient.

4. The aviation obstruction light malfunction early warning method according to claim 3, characterized in that, Calculate and analyze the average DC bus voltage Vd of the obstruction lamps at each sampling point during the analysis period; Subtract Vd from the bus voltage at each sampling point within the analysis period to obtain the ripple voltage at that sampling point. Calculate the root mean square value of the ripple voltage within the analysis period, denoted as Vr. The voltage ripple factor RF is determined based on Vd and Vr, where RF = Vr / Vd; Compare RF with a preset voltage ripple threshold r0 to determine the first electrical characteristic D1: when RF is less than or equal to r0, determine D1 as 0; otherwise, determine D1 = ln[5×(RF-r0)+1] / ln6; The second electrical characteristic D2 is determined based on the power factor PF during the analysis period, where D2 = (P0 - PF) / P0; The electrical characteristic Dz of the obstruction light is determined by combining the first electrical characteristic D1 and the second electrical characteristic D2, where Dz = r1 × D1 + r2 × D2; Where r1 is the first electrical weight, r2 is the second electrical weight, P0 is the preset power factor, and r1+r2=1.

5. The aviation obstruction light malfunction early warning method according to claim 4, characterized in that, The humidity s0 of the obstruction light sealing cavity is compared with the preset humidity s1 to determine the obstruction light sealing degradation characteristic LD. If s0 is less than or equal to the preset humidity s1, the obstruction light sealing degradation characteristic LD is determined to be 0. If s0 is greater than the preset humidity s1, the obstruction light sealing degradation characteristic LD is determined to be min(1,(s0-s1) / △s); where △s is the preset humidity difference. The comprehensive deterioration index Lz is determined by combining the electrical characteristics Dz and the sealing deterioration characteristics LD of the obstacle light, where Lz = u1 × Dz + u2 × LD; Where u1 is the electrical characteristic weight, u2 is the sealing degradation weight, and u1+u2=1.

6. The aviation obstruction light malfunction early warning method according to claim 5, characterized in that, The vibration anomaly characteristic ZU is compared with the preset anomaly coefficient z0. When ZU is greater than z0, the electrical characteristic weight is adjusted to 0.8×u1 and the sealing deterioration weight is adjusted to (1-0.8×u1) to adjust the determination process of the comprehensive deterioration index. Otherwise, the electrical characteristic weight and sealing deterioration weight are not adjusted. The adjusted comprehensive degradation index is set to Lzt. If Lzt is less than or equal to the preset warning threshold, no warning will be issued to the user regarding the degradation of the obstruction lights; otherwise, a warning will be issued to the user regarding the degradation of the obstruction lights.

7. The aviation obstruction light malfunction early warning method according to claim 6, characterized in that, Based on the salt spray erosion intensity, abnormal vibration characteristics, and obstruction light deterioration warnings during the fault detection cycle, fault risk factors are determined, and fault maintenance alarms are issued to users. At the same time, the overcurrent protection threshold for the next fault detection cycle is adjusted according to the fault risk factors.

8. The aviation obstruction light malfunction early warning method according to claim 7, characterized in that, The number of analysis cycles in which the salt spray erosion intensity SE is greater than the salt spray erosion intensity threshold sy within the fault detection cycle is denoted as k1. The number of analysis cycles in which the vibration anomaly characteristic ZU is greater than the preset anomaly coefficient z0 within the fault detection cycle is counted and denoted as k2; The number of analysis cycles during which warnings of obstruction light deterioration are issued to users within the statistical fault monitoring cycle is denoted as k3; Based on k1, k2 and k3, the risk factor Fv is determined. When the risk factor Fv is greater than the preset risk threshold Ff, a fault repair alarm is issued to the user; otherwise, no fault repair warning is issued to the user. When the risk factor Fv is less than or equal to the preset risk threshold Ff, the overcurrent protection threshold Ibase for the next fault detection cycle is set to max(Ibmin,Ibase×(1-γ×(Fv-Ff))). Where γ is the preset adjustment coefficient, Ibase is the overcurrent protection reference threshold, and Ibmin is the minimum protection threshold.

9. An aviation obstruction light malfunction early warning device, applied to the aviation obstruction light malfunction early warning method as described in any one of claims 1-8, characterized in that, include: The erosion analysis unit is used to determine the salt spray erosion intensity based on the salt spray concentration at the top, middle, and bottom of the tower. The feature extraction unit is used to extract vibration intensity and dominant vibration frequency based on triaxial vibration acceleration, and then determine vibration frequency distribution characteristics, and determine vibration anomaly characteristics based on vibration intensity and vibration frequency distribution characteristics; The degradation determination unit is used to determine the electrical characteristics of the obstruction lamp based on the DC bus voltage of the obstruction lamp and the power factor of the obstruction lamp drive circuit, determine the sealing degradation characteristics of the obstruction lamp based on the humidity of the obstruction lamp sealing cavity, and determine the comprehensive degradation index based on the electrical characteristics and sealing degradation characteristics of the obstruction lamp. The early warning unit is used to adjust the process of determining the comprehensive degradation index based on the abnormal vibration characteristics, determine the degradation status of the obstruction lights based on the adjusted comprehensive degradation index, and provide the user with an early warning of obstruction light degradation. The fault detection unit is used to determine the fault risk factors based on the salt spray erosion intensity, abnormal vibration characteristics, and obstruction light deterioration warnings during the fault detection cycle, and to issue a fault maintenance alarm to the user. At the same time, it adjusts the overcurrent protection threshold for the next fault detection cycle based on the fault risk factors.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program is used to control the electronic device on which the computer-readable storage medium is located to perform the aviation obstruction light malfunction warning method according to any one of claims 1-8 during runtime.

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