A spectral identification and position calibration system for aircraft connectors

Abstract

This invention discloses a spectral identification and position calibration system for aircraft connectors. The system comprises: a spectral identification module acquiring spectral data of the aircraft connector; an adaptive noise filtering module removing environmental noise from the spectral data using an adaptive noise filtering algorithm; a data processing module identifying the material and characteristics of the aircraft connector based on the noise-free spectral data; a thermal deformation prediction and compensation module predicting the thermal deformation of the connector based on a thermodynamic model and real-time temperature monitoring data obtained from temperature sensors, and performing real-time thermal deformation compensation; a position calibration module calibrating the position of the aircraft connector based on the identification results of its material and characteristics, combined with the thermal deformation compensation results from the thermal deformation prediction and compensation module; and a control and display module executing the control and calibration process of the aircraft connector and displaying the spectral identification results and the position calibration results. The technical solution provided by this invention solves the problems of low identification accuracy, inability to predict and compensate for connector deformation caused by temperature changes in real time, and difficulty in guaranteeing the accuracy and stability of calibration results in existing detection and calibration methods for aircraft connectors.

Description

Technical Field

[0001] This invention relates to, but is not limited to, the field of aircraft structure inspection technology, and particularly to a spectral identification and position calibration system for aircraft connectors. Background Technology

[0002] In the aerospace field, aircraft connectors are critical components ensuring the structural stability and safety of aircraft. These connectors operate in high-temperature, high-humidity, and other extreme environments, requiring extremely high stability and precise assembly. Traditional testing and calibration methods for aircraft connectors mainly rely on manual inspection and basic measuring instruments. However, due to the influence of environmental factors and material properties on testing accuracy, traditional methods often face challenges in practical applications, including environmental noise interference, thermal deformation caused by temperature changes, and the impact of changes in material properties on the identification results.

[0003] Currently, existing testing and calibration methods for aircraft connectors have the following shortcomings: First, traditional spectral recognition technology often fails to accurately extract the spectral data of connectors under the influence of environmental noise, resulting in low recognition accuracy. Second, for thermal deformation issues, existing technologies typically rely on static measurements and simple compensation methods, which cannot predict and compensate for connector deformation caused by temperature changes in real time. In addition, existing systems often ignore the combined effects of material properties and thermal deformation during position calibration, making it difficult to guarantee the accuracy and stability of the final calibration results. These shortcomings affect the testing accuracy of aircraft connectors and the overall reliability of the system. Summary of the Invention

[0004] The purpose of this invention is to solve the above-mentioned technical problems. This invention provides a spectral recognition and position calibration system for aircraft connectors, which solves the problems of low recognition accuracy, inability to predict and compensate for connector deformation caused by temperature changes in real time, and difficulty in guaranteeing the accuracy and stability of calibration results in existing detection and calibration methods for aircraft connectors.

[0005] The technical solution of the present invention: The present invention provides a spectral recognition and position calibration system for aircraft connectors, comprising: a spectral recognition module, an adaptive noise filtering module, a data processing module, a position calibration module and a control and display module connected in sequence, a thermal deformation prediction and compensation module connected to the position calibration module, and a plurality of temperature sensors electrically connected to the thermal deformation prediction and compensation module;

[0006] The spectral recognition module is used to acquire the spectral data of the aircraft connectors;

[0007] The adaptive noise filtering module is used to remove environmental noise from the spectral data obtained by the spectral recognition module based on an adaptive noise filtering algorithm.

[0008] The data processing module is used to identify the material and characteristics of aircraft connectors based on spectral data after removing environmental noise.

[0009] The thermal deformation prediction and compensation module is used to predict the thermal deformation of the connector based on a thermodynamic model and real-time temperature monitoring data obtained by temperature sensors, and to perform real-time thermal deformation compensation for the aircraft connector; the processing method of the thermal deformation prediction and compensation module includes:

[0010] Sa, Temperature Monitoring: The temperature of the aircraft connector is monitored in real time by multiple temperature sensors arranged on the aircraft connector.

[0011] Sb, Thermodynamic Modeling: Establishing a thermodynamic model of the connector to predict its thermal deformation behavior under different temperature conditions;

[0012] Sc, Real-time Analysis: Input the temperature of the aircraft connectors monitored in real time into the thermodynamic model to calculate the real-time thermal deformation.

[0013] Sd, thermal deformation compensation: Generates compensation instructions based on the calculated thermal deformation amount;

[0014] Se, Execution Feedback: Perform thermal deformation compensation according to the generated compensation instructions, and monitor the compensation effect in real time;

[0015] The position calibration module is used to calibrate the position of the aircraft connector based on the identification results of the material and characteristics of the aircraft connector by the data processing module and the thermal deformation compensation results of the aircraft connector by the thermal deformation prediction and compensation module.

[0016] The control and display module is used to execute the control calibration process of the aircraft connector and to display the spectral recognition results and position calibration results.

[0017] Optionally, in the spectral recognition and position calibration system for aircraft connectors as described above, the spectral recognition module includes: a light source unit, a spectral sensor, and a scanning unit;

[0018] The light source unit is used to emit a light beam within a predetermined wavelength range onto the surface of the aircraft connector.

[0019] The spectral sensor is used to receive light beams reflected or transmitted from the surface of the aircraft connector and convert them into spectral signals;

[0020] The scanning unit is used to control the movement of the light source unit and the spectral sensor to perform a comprehensive spectral scan of the entire surface of the aircraft connector.

[0021] Optionally, in the spectral identification and position calibration system for aircraft connectors as described above, the adaptive noise filtering module includes: a noise sensor and an adaptive filter; the adaptive noise filtering module executes the adaptive noise filtering algorithm in the following ways:

[0022] S11, Initialization: Set the initial filter coefficients w(0) to a zero vector, and the learning rate μ to a positive number, expressed as:

[0023] w(0) = 0, μ > 0;

[0024] S12, Noise monitoring: Record the environmental noise signal x(n) in real time using a noise sensor;

[0025] S13, Spectral data recording: Record spectral data d(n) containing noise;

[0026] S14, Noise Estimation: Estimate the noise signal by outputting an adaptive filter. Represented as:

[0027]

[0028] Where, w(n) T It is the transpose of the adaptive filter coefficient vector at the nth iteration time;

[0029] S15, Error Signal Calculation: Calculate the difference between the actual spectral data and the estimated noise signal, expressed as:

[0030]

[0031] Where e(n) is the error signal at the nth iteration time;

[0032] S16, Filter coefficient update: Update the filter coefficients w(n) according to the error signal, expressed as:

[0033] w(n+1)=w(n)+vx(n)e(n);

[0034] Where w(n+1) is the adaptive filter coefficient vector at the (n+1)th iteration, w(n) is the adaptive filter coefficient vector at the nth iteration, and μx(n)e(n) is the amount adjusted according to the current environmental noise signal and error signal.

[0035] Optionally, in the spectral identification and position calibration system for aircraft connectors as described above, the data processing module processes data in the following ways:

[0036] S21, Spectral data preprocessing: Normalize the spectral data after removing environmental noise;

[0037] S22, Feature Extraction: Extract key features from the normalized spectral data, including peak position, peak intensity, and full width at half maximum (FWHM), expressed as:

[0038] λ peak =argmax λ d norm (λ);

[0039] I peak =max λ d norm (λ);

[0040] FWHM = λ2 - λ1;

[0041] Where, λ peak It is the peak position, I peak It is the peak intensity, FWHM is the full width at half maximum (FWHM), λ is the wavelength, and d is the peak intensity. norm (λ) is the intensity value of the normalized spectral data at wavelength λ, and λ1 and λ2 are the spectral intensities that are half the peak intensity (I). peak The wavelength position corresponding to / 2);

[0042] S23, Classification and Recognition: Use the support vector machine algorithm to classify the extracted key features and identify the material and characteristics of aircraft connectors.

[0043] Optionally, in the spectral identification and position calibration system for aircraft connectors as described above, multiple temperature sensors are pre-arranged at different locations on the aircraft connectors; the thermal deformation prediction and compensation module performs temperature monitoring in the following ways:

[0044] S-a1, Data Acquisition: Temperature data is periodically collected from each temperature sensor, represented as:

[0045] T i (t)=T i (t);

[0046] Among them, T i (t) is the temperature data recorded by the temperature sensor at position i at time t;

[0047] S-a2, Temperature Data Analysis: The collected temperature data is analyzed to generate an overall temperature distribution map of the aircraft connectors, represented as follows:

[0048] T dist = f(T1(t),T2(t),...,T n (t));

[0049] Among them, T dist This is the overall temperature distribution diagram of the connector, and f(·) is the temperature distribution calculation function.

[0050] Optionally, in the spectral identification and position calibration system for aircraft connectors as described above, the thermodynamic model adopts a thermohydrodynamic model, and the thermal deformation prediction and compensation module performs thermodynamic modeling in the following ways:

[0051] S-b1, initialization and mesh generation, includes: 3D modeling of the aircraft connectors and decomposing them into multiple finite volume elements using mesh generation techniques, represented as:

[0052]

[0053] Where Ω is the global domain of the connector, Ω i It is the i-th finite volume element, and N is the total number of elements;

[0054] S-b2, establish the fluid motion equations, including: describing the flow behavior of the fluid on the surface of the aircraft connector, expressed as:

[0055]

[0056] Where u is the fluid velocity, p is the pressure, μ is the dynamic viscosity, and f is the body force;

[0057] S-b3 establishes an energy equation to describe the heat transfer and temperature change between the fluid and the aircraft connection, expressed as:

[0058]

[0059] Where ρ is density, c p It is the specific heat capacity at constant pressure, T is the temperature, k is the thermal conductivity, and Q is the internal heat source;

[0060] S-b4 establishes a solid thermal stress equation to describe the stress-strain relationship of aircraft connectors under temperature changes, expressed as:

[0061] σ ij =C ijkl (∈ kl -α kl ΔT);

[0062] Where, σ ij It is the stress tensor, C ijkl It is the elastic modulus, ∈ kl It is the strain tensor, α kl ΔT is the coefficient of thermal expansion, and ΔT is the change in temperature.

[0063] S-b5 sets interfacial coupling conditions for the solid thermal stress equation to describe the interfacial heat exchange and thermal stress transfer between the fluid and aircraft connectors, expressed as:

[0064] qinterface =h(T) f -T s );

[0065] Where, q interface It is the interfacial heat flux, h is the convective heat transfer coefficient, and T is the interfacial heat flux. f It is the fluid temperature, T s It is the surface temperature of the solid;

[0066] S-b6, Iterative solution: The numerical iterative method is used to solve the equations from S-b2 to S-b5 to obtain the temperature field and stress field of the fluid and aircraft connection parts;

[0067] The temperature field is represented as:

[0068]

[0069] Among them, T n+1 It is the temperature field at the (n+1)th iteration, T n This is the temperature field at the nth iteration, where Δt is the time step, α is the thermal diffusivity, Q is the internal heat source, and u... n It is the fluid velocity at the nth iteration time;

[0070] The stress field is represented as:

[0071]

[0072] in, It is the stress tensor at the (n+1)th iteration. It is the strain tensor at the (n+1)th iteration, α kl It is the coefficient of thermal expansion, ΔT n+1 It represents the temperature change at the (n+1)th iteration.

[0073] Optionally, in the spectral identification and position calibration system for aircraft connectors as described above, the thermal deformation prediction and compensation module performs real-time analysis in the following ways:

[0074] S-c1, Temperature Data Input: Input the temperature data {T} monitored by each temperature sensor. i (t)} is input into the thermodynamic model of the thermal fluid in real time;

[0075] S-c2, Solving the thermodynamic model: Based on the input temperature data, the temperature field T(t) and stress field σ(t) of the aircraft connector are calculated using the thermodynamic model.

[0076] S-c3, Calculation of thermal deformation: By solving for the temperature field and stress field, the real-time thermal deformation ΔL of the aircraft connector is calculated, expressed as:

[0077] ΔL=αL0ΔT;

[0078] Where ΔL is the length change, α is the coefficient of thermal expansion, L0 is the initial length, and ΔT is the temperature change.

[0079] Optionally, in the spectral identification and position calibration system for aircraft connectors as described above, the thermal deformation prediction and compensation module performs thermal deformation compensation in the following ways:

[0080] S-d1, Thermal Deformation Input: Receives the calculated thermal deformation ΔL;

[0081] S-d2, Calculate compensation parameters: Calculate the required compensation parameters based on the thermal deformation, including displacement and angle adjustments, expressed as:

[0082] C displacement =β displacement ΔL;

[0083] Among them, C displacement β is the displacement compensation parameter. displacement ΔL is the displacement compensation coefficient, and ΔL is the thermal deformation.

[0084] C angle =β angle ΔL;

[0085] Among them, C angle β is the angle compensation parameter. angle ΔL is the angle compensation coefficient, and ΔL is the thermal deformation.

[0086] S-d3, Compensation Command Generation: Compensation commands are generated based on compensation parameters and temperature monitoring results. These commands include position adjustment commands, angle adjustment commands, stress release commands, temperature control commands, and mechanical correction commands. The stress release commands are obtained by adjusting displacement and angle caused by thermal deformation and material property changes of aircraft connectors. The temperature control commands are generated based on real-time temperature monitoring results. The mechanical correction commands are obtained by physical correction of the overall mechanical system based on a comprehensive consideration of position, angle, stress, and temperature factors.

[0087] Optionally, in the spectral identification and position calibration system for aircraft connectors as described above, the thermal deformation prediction and compensation module performs feedback in the following ways:

[0088] S-e1, Compensation Execution: Execute the actual compensation operation according to the compensation instruction;

[0089] S-e2, Effect Monitoring: Real-time monitoring of compensation effect, collection of status data after compensation;

[0090] S-e3, Effect Evaluation: Analyze the compensated state data and compare it with the target state. Use root mean square error to evaluate the compensation effect.

[0091] S-e4, Feedback Adjustment: Adjust compensation parameters and compensation instructions based on the results of the effect evaluation.

[0092] Optionally, in the spectral identification and position calibration system for aircraft connectors as described above, the position calibration module calibrates the position of the aircraft connector in the following ways:

[0093] S31, Obtain material and property data: Obtain material property data and spectral identification results for aircraft connectors;

[0094] S32, acquire thermal deformation compensation data;

[0095] S33, Position Calibration: Using the position calibration formula, the material and properties of the aircraft connectors, as well as thermal deformation compensation data, are used as inputs to calculate the calibration position P. cal , is represented as:

[0096] P cal =P measured +ΔP mat +ΔP therm ;

[0097] Among them, P cal For the calibrated aircraft connector positions, P measured For the original measurement position, ΔP mat For calibration quantities based on material and properties, ΔP therm This is a calibration amount based on thermal deformation;

[0098] ΔP mat =k mat ·(TT ref );

[0099] ΔP therm =k therm ·D;

[0100] Where, k mat Here is the material property calibration coefficient, and T is the actual temperature. ref For reference temperature, k therm Here, D is the thermal deformation compensation coefficient, and D is the thermal deformation compensation data.

[0101] S34, Perform position calibration: based on the calculated calibration position P cal Adjust the position of the aircraft connectors.

[0102] The beneficial effects of the present invention are as follows: The embodiments of the present invention provide a spectral identification and position calibration system for aircraft connectors. On the one hand, by combining a spectral identification module with an adaptive noise filtering algorithm, the system can effectively remove the interference of environmental noise on spectral data, thereby improving the accuracy and reliability of spectral data. This process ensures the accurate identification of the material and characteristics of aircraft connectors, providing a solid data foundation for subsequent thermal deformation compensation and position calibration. The adaptive noise filtering algorithm has the ability to dynamically adjust the filtering coefficient, which can adapt to different noise environments in real time, further improving the accuracy of spectral identification.

[0103] On the other hand, by monitoring the temperature of the connectors in real time and combining thermodynamic modeling to accurately calculate thermal deformation at different temperatures, the system can generate effective compensation commands, including displacement, angle adjustment, stress release, etc., ensuring the accurate position and functional stability of the connectors under different temperature conditions. The feedback mechanism in the compensation process also optimizes the compensation effect, reduces errors, and improves the stability and reliability of the system through real-time monitoring and effect evaluation.

[0104] On the other hand, through comprehensive analysis of material properties and thermal deformation data, the system can achieve high-precision adjustment of connector positions, ensuring accurate assembly of connectors in actual working environments. This calibration process significantly improves the efficiency of aircraft maintenance and manufacturing, optimizes the assembly quality of aircraft connectors, and enhances the performance and safety of aircraft under various working conditions. Attached Figure Description

[0105] The accompanying drawings are provided to further understand the technical solutions of the present invention and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of the present invention and do not constitute a limitation on the technical solutions of the present invention.

[0106] Figure 1 A schematic diagram of the overall structure of a spectral identification and position calibration system for aircraft connectors provided in an embodiment of the present invention;

[0107] Figure 2 for Figure 1 The illustrated embodiment provides a schematic diagram of the workflow of the thermal deformation prediction and compensation module in a spectral identification and position calibration system for aircraft connectors. Detailed Implementation

[0108] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

[0109] As explained in the background section above, aircraft connectors are crucial to aircraft structures and require high stability and precise assembly during use. This necessitates the testing and calibration of aircraft connectors, and the existing testing and calibration methods for aircraft connectors present numerous problems.

[0110] To address the numerous problems with existing testing and calibration methods for aircraft connectors, this invention provides a spectral identification and position calibration system for aircraft connectors. This system effectively addresses the impact of environmental noise and temperature changes on the testing accuracy of aircraft connectors, ensuring stability and reliability under various operating conditions, thereby improving the efficiency and quality of aircraft maintenance and manufacturing.

[0111] The present invention provides the following specific embodiments, which can be combined with each other. For the same or similar concepts or processes, they may not be described again in some embodiments.

[0112] Figure 1 This is a schematic diagram of the overall structure of a spectral identification and position calibration system for aircraft connectors, provided as an embodiment of the present invention. Figure 1 As shown, the spectral recognition and position calibration system for aircraft connectors provided in this embodiment of the invention includes: a spectral recognition module, an adaptive noise filtering module, a data processing module, a position calibration module, and a control and display module connected in sequence; a thermal deformation prediction and compensation module connected to the position calibration module; and multiple temperature sensors electrically connected to the thermal deformation prediction and compensation module.

[0113] like Figure 1 In the system shown, the spectral recognition module in this embodiment of the invention is used to acquire the spectral data of the aircraft connector.

[0114] The adaptive noise filtering module in this embodiment of the invention is used to remove environmental noise from the spectral data obtained by the spectral recognition module based on an adaptive noise filtering algorithm.

[0115] The data processing module in this embodiment of the invention is used to identify the material and characteristics of aircraft connectors based on spectral data after removing environmental noise.

[0116] The thermal deformation prediction and compensation module in this embodiment of the invention is used to predict the thermal deformation of the connector based on a thermodynamic model and temperature monitoring data obtained in real time by using a temperature sensor, and to perform real-time thermal deformation compensation for the aircraft connector. Figure 2 for Figure 1 The illustrated embodiment provides a schematic diagram of the workflow of the thermal deformation prediction and compensation module in a spectral identification and position calibration system for aircraft connectors; the processing method of this thermal deformation prediction and compensation module includes:

[0117] Sa, Temperature Monitoring: The temperature of the aircraft connector is monitored in real time by multiple temperature sensors arranged on the aircraft connector.

[0118] Sb, Thermodynamic Modeling: Establishing a thermodynamic model of the connector to predict its thermal deformation behavior under different temperature conditions;

[0119] Sc, Real-time Analysis: Input the temperature of the aircraft connectors monitored in real time into the thermodynamic model to calculate the real-time thermal deformation.

[0120] Sd, thermal deformation compensation: Generates compensation instructions based on the calculated thermal deformation amount;

[0121] Se, Execution Feedback: Perform thermal deformation compensation according to the generated compensation instructions, and monitor the compensation effect in real time.

[0122] The position calibration module in this embodiment of the invention is used to calibrate the position of the aircraft connector based on the identification results of the material and characteristics of the aircraft connector by the data processing module and the thermal deformation compensation results of the aircraft connector by the thermal deformation prediction and compensation module.

[0123] The control and display module in this embodiment of the invention is used to execute the control calibration process of the aircraft connector and to display the spectral recognition results and the position calibration results.

[0124] The spectral identification and position calibration system for aircraft connectors provided in this invention achieves high-precision and high-reliability aircraft connector detection and calibration through the functions implemented by the above-mentioned functional modules. It can effectively cope with the impact of environmental noise and temperature changes on detection accuracy, and ensure stability and reliability under various working conditions, thereby improving the efficiency and quality of aircraft maintenance and manufacturing.

[0125] In one implementation of this invention, the spectral recognition module includes: a light source unit, a spectral sensor, and a scanning unit. The functions of each unit in this implementation are described below:

[0126] A light source unit is used to emit a light beam within a predetermined wavelength range onto the surface of the aircraft connector;

[0127] A spectral sensor is used to receive light beams reflected or transmitted from the surface of aircraft connectors and convert them into spectral signals;

[0128] The scanning unit controls the movement of the light source unit and the spectral sensor to perform a comprehensive spectral scan of the entire surface of the aircraft connector.

[0129] In this implementation, the aforementioned functional units not only improve the coverage and accuracy of spectral data, but also ensure the comprehensiveness and consistency of the data, providing a reliable foundation for subsequent analysis, processing, and position calibration, and significantly improving the system's detection efficiency and accuracy.

[0130] In one implementation of this invention, the adaptive noise filtering module includes: a noise sensor and an adaptive filter; the adaptive noise filtering module executes the adaptive noise filtering algorithm in the following ways:

[0131] S11, Initialization: Set the initial filter coefficients w(0) to a zero vector, and the learning rate μ to a positive number, expressed as:

[0132] w(0) = 0, μ > 0;

[0133] S12, Noise monitoring: Record the environmental noise signal x(n) in real time using a noise sensor;

[0134] S13, Spectral data recording: Record spectral data d(n) containing noise;

[0135] S14, Noise Estimation: Estimate the noise signal by outputting an adaptive filter. Represented as:

[0136]

[0137] Where, w(n) T It is the transpose of the adaptive filter coefficient vector at the nth iteration time;

[0138] S15, Error Signal Calculation: Calculate the difference between the actual spectral data and the estimated noise signal, expressed as:

[0139]

[0140] Where e(n) is the error signal at the nth iteration time;

[0141] S16, Filter coefficient update: Update the filter coefficients w(n) according to the error signal, expressed as:

[0142] w(n+1)=w(n)+μx(n)e(n);

[0143] Where w(n+1) is the adaptive filter coefficient vector at the (n+1)th iteration, w(n) is the adaptive filter coefficient vector at the nth iteration, and μx(n)e(n) is the amount adjusted according to the current environmental noise signal and error signal.

[0144] In this implementation, the adaptive noise filtering module executes the aforementioned steps of the adaptive noise filtering algorithm, enabling real-time monitoring of environmental noise and dynamic adjustment of filter coefficients to remove environmental noise from the spectral data. By initializing the filter coefficients and setting the learning rate, the system can adapt to different noise environments and progressively optimize the filtering effect. The environmental noise signal recorded by the noise sensor and the spectral data recorded by the spectral sensor are combined, and the noise signal is estimated and the error signal is calculated through the adaptive filter. Finally, the filter coefficients are adjusted to ensure filtering accuracy and the reliability of spectral recognition.

[0145] In one implementation of this invention, the data processing module's processing method includes the following steps:

[0146] S21, Spectral data preprocessing: The spectral data after removing environmental noise is normalized to reduce the impact of fluctuations in spectral intensity, as shown below:

[0147]

[0148] Where d(i) is the intensity value of the noise-removed spectral data at wavelength i, d norm (i) represents the intensity value of the normalized spectral data at wavelength i, and min(d) and max(d) represent the minimum and maximum values ​​of the spectral data after noise removal.

[0149] S22, Feature Extraction: Extract key features from the normalized spectral data, including peak position, peak intensity, and full width at half maximum (FWHM), expressed as:

[0150] λ peak =argmax λ d norm (λ);

[0151] I peak =max λ d norm (λ);

[0152] FWHM = λ2 - λ1;

[0153] Where, λ peak It is the peak position, I peak It is the peak intensity, FWHM is the full width at half maximum (FWHM), λ is the wavelength, and d is the peak intensity. norm (λ) is the intensity value of the normalized spectral data at wavelength λ, and λ1 and λ2 are the spectral intensities that are half the peak intensity (I). peak The wavelength position corresponding to / 2);

[0154] S23, Classification and Recognition: Using a support vector machine algorithm, the extracted key features are classified to identify the material and properties of aircraft connectors, represented as follows:

[0155]

[0156] Where x is the input feature vector, N is the number of training samples, and α i It is a Lagrange multiplier, y i These are the labels (material and characteristics) of the training samples, K(x) i ,x) is the radial basis function (RBF) kernel function.

[0157] In this implementation, the data processing module executes the above-mentioned processing steps, which improves the accuracy and reliability of spectral identification, effectively identifies the material and characteristics of aircraft connectors, and significantly improves the accuracy and efficiency of detection.

[0158] In one implementation of this invention, multiple temperature sensors are pre-arranged at different locations on the aircraft connector; based on the arrangement of the temperature sensors, the thermal deformation prediction and compensation module performs temperature monitoring in the following ways:

[0159] S-a1, Data Acquisition: Temperature data is periodically collected from each temperature sensor, represented as:

[0160] T i (t)=T i (t);

[0161] Among them, T i (t) is the temperature data recorded by the temperature sensor at position i at time t;

[0162] S-a2, Temperature Data Analysis: The collected temperature data is analyzed to generate an overall temperature distribution map of the aircraft connectors, represented as follows:

[0163] T dist = f(T1(t),T2(t),...,T n (t));

[0164] Among them, T dist This is the overall temperature distribution diagram of the connector, and f(·) is the temperature distribution calculation function.

[0165] In this implementation, the temperature distribution calculation function, for example using a linear interpolation algorithm, can be expressed as:

[0166]

[0167] Among them, T dist (x) is the interpolated temperature at position x, T iThis is the position and temperature data of the i-th sensor, w i (x) is the weight associated with the i-th sensor at position x, satisfying...

[0168] weight w i (x) is calculated using the inverse distance weighting method based on sensor location, and is expressed as:

[0169]

[0170] Where, d i (x) is the distance between position x and the position of the i-th sensor, and p is the distance parameter with a value of 2.

[0171] In this implementation, by performing the above-mentioned temperature monitoring steps, the temperature of different key locations of the aircraft connector is monitored in real time. Combined with the data acquisition and processing unit, an overall temperature distribution map is generated. Interpolation algorithms such as linear interpolation are used to achieve the fusion and analysis of temperature data, ensuring the accuracy and comprehensiveness of temperature monitoring. This effectively improves the real-time response capability and accuracy of the system, and ensures the stability and reliability of the aircraft connector under different temperature conditions.

[0172] In one implementation of this invention, the thermodynamic model adopts a thermohydrodynamic model; the thermal deformation prediction and compensation module performs thermodynamic modeling by including the following steps:

[0173] S-b1, initialization and mesh generation, includes: 3D modeling of the aircraft connectors and decomposing them into multiple finite volume elements using mesh generation techniques, represented as:

[0174]

[0175] Where Ω is the global domain of the connector, Ω i It is the i-th finite volume element, and N is the total number of elements;

[0176] S-b2, establish the fluid motion equations, including: describing the flow behavior of the fluid on the surface of the aircraft connector, expressed as:

[0177]

[0178] Where u is the fluid velocity, p is the pressure, μ is the dynamic viscosity, and f is the body force;

[0179] S-b3 establishes an energy equation to describe the heat transfer and temperature change between the fluid and the aircraft connection, expressed as:

[0180]

[0181] Where ρ is density, cp It is the specific heat capacity at constant pressure, T is the temperature, k is the thermal conductivity, and Q is the internal heat source;

[0182] S-b4 establishes a solid thermal stress equation to describe the stress-strain relationship of aircraft connectors under temperature changes, expressed as:

[0183] σ ij =C ijkl (∈ kl -α kl ΔT);

[0184] Where, σ ij It is the stress tensor, C ijkl It is the elastic modulus, ∈ kl It is the strain tensor, α kl ΔT is the coefficient of thermal expansion, and ΔT is the change in temperature.

[0185] S-b5 sets interfacial coupling conditions for the solid thermal stress equation to describe the interfacial heat exchange and thermal stress transfer between the fluid and aircraft connectors, expressed as:

[0186] q interface =h(T) f -T s );

[0187] Where, q interface It is the interfacial heat flux, h is the convective heat transfer coefficient, and T is the interfacial heat flux. f It is the fluid temperature, T s It is the surface temperature of the solid;

[0188] S-b6, Iterative solution: The numerical iterative method is used to solve the equations from S-b2 to S-b5 to obtain the temperature field and stress field of the fluid and aircraft connection parts;

[0189] The temperature field is represented as:

[0190]

[0191] Among them, T n+1 It is the temperature field at the (n+1)th iteration, T n This is the temperature field at the nth iteration, where Δt is the time step, α is the thermal diffusivity, Q is the internal heat source, and u... n It is the fluid velocity at the nth iteration time;

[0192] The stress field is represented as:

[0193]

[0194] in, It is the stress tensor at the (n+1)th iteration. It is the strain tensor at the (n+1)th iteration, α kl It is the coefficient of thermal expansion, ΔT n+1 It is the temperature change at the (n+1)th iteration.

[0195] In this implementation, by performing the above steps of thermodynamic modeling, the aircraft connector is decomposed into multiple finite volume elements through mesh generation. The Navier-Stokes equations are used to describe fluid motion, the heat conduction equation is used to simulate heat exchange between the fluid and the solid, and the solid thermal stress equation is introduced to describe the stress-strain relationship of the connector under temperature changes. Through interface coupling conditions, the fluid temperature and solid temperature are coupled and calculated. The above equations are solved using numerical iteration methods, and finally, the accurate temperature field and stress field distribution are obtained. This can more accurately simulate the thermal deformation behavior of the aircraft connector under complex thermal environments, providing accurate data support for subsequent thermal deformation compensation and improving the prediction accuracy and reliability of the system.

[0196] In one implementation of this invention, the thermal deformation prediction and compensation module performs real-time analysis in the following ways:

[0197] S-c1, Temperature Data Input: Input the temperature data {T} monitored by each temperature sensor. i (t)} is input into the thermodynamic model of the thermal fluid in real time;

[0198] S-c2, Solving the thermodynamic model: Based on the input temperature data, the temperature field T(t) and stress field σ(t) of the aircraft connector are calculated using the thermodynamic model.

[0199] S-c3, Calculation of thermal deformation: By solving for the temperature field and stress field, the real-time thermal deformation ΔL of the aircraft connector is calculated, expressed as:

[0200] ΔL=αL0ΔT;

[0201] Where ΔL is the length change, α is the coefficient of thermal expansion, L0 is the initial length, and ΔT is the temperature change.

[0202] In this implementation, by performing the above-mentioned steps of real-time analysis, the system's responsiveness to changes in complex thermal environments is improved, accurate data support is provided, and the accuracy and reliability of thermal deformation compensation are effectively improved, thereby ensuring the stability and safety of aircraft connectors under various working conditions.

[0203] In one implementation of this invention, the thermal deformation prediction and compensation module performs thermal deformation compensation by the following steps:

[0204] S-d1, Thermal Deformation Input: Receives the calculated thermal deformation ΔL;

[0205] S-d2, Calculate compensation parameters: Calculate the required compensation parameters based on the thermal deformation, including displacement and angle adjustments, expressed as:

[0206] C displacement =β displacement ΔL;

[0207] Among them, C displacement Here, β is the displacement compensation parameter, representing the amount of displacement to be applied. displacement ΔL is the displacement compensation coefficient, which represents the proportionality of the displacement compensation required per unit of thermal deformation. ΔL is the thermal deformation, which represents the change in the length of the connector due to temperature changes.

[0208] C angle =β angle ΔL;

[0209] Among them, C angle β is the angle compensation parameter, representing the amount of angle adjustment that needs to be applied. angle ΔL is the angle compensation coefficient, which represents the proportionality of the angle compensation required per unit of thermal deformation. ΔL is the thermal deformation, which represents the change in the length of the connector due to temperature changes.

[0210] S-d3, Compensation Command Generation: Based on compensation parameters and temperature monitoring results, compensation commands are generated. These commands include position adjustment commands (for displacement compensation), angle adjustment commands (for rotational compensation), stress relief commands, temperature control commands, and mechanical correction commands (physical adjustments via actuators). The stress relief command is obtained through displacement and angle adjustments caused by thermal deformation and material property changes in aircraft connectors. The temperature control command is generated based on real-time temperature monitoring results. The mechanical correction command is obtained through physical correction of the entire mechanical system, taking into account position, angle, stress, and temperature factors. The generation method and function of each command are explained below:

[0211] Position adjustment command: The command generated by combining displacement compensation and angle compensation is used to precisely adjust the position of the connector to ensure that it can return to the predetermined state after thermal deformation compensation;

[0212] Angle adjustment command: A command generated based on angle compensation parameters, used to adjust the installation angle of the connector to ensure its correct orientation;

[0213] Stress relief instruction: During the compensation process, the displacement and angle adjustments caused by thermal deformation and changes in material properties are released in a timely manner to release the additional stress on the connectors caused by these adjustments, so as to prevent material damage or fatigue.

[0214] Temperature control command: The command is generated based on the real-time temperature monitoring results to adjust the temperature of the connector to ensure that the material is within the appropriate working range in order to maintain its performance;

[0215] Mechanical calibration instructions: Taking into account factors such as position, angle, stress, and temperature, perform physical calibration of the entire mechanical system to ensure the correct alignment and normal function of each component.

[0216] In this implementation method, by performing the above-mentioned steps of thermal deformation compensation, the error caused by thermal deformation is effectively reduced, thereby improving the reliability and stability of the overall system. This precise compensation mechanism not only enhances the maintenance efficiency of the aircraft, but also improves the safety and performance of the aircraft in various operating environments.

[0217] In one implementation of this invention, the feedback method performed by the thermal deformation prediction and compensation module may include the following steps:

[0218] S-e1, Compensation Execution: Execute the actual compensation operation according to the compensation instruction;

[0219] S-e2, Effect Monitoring: Real-time monitoring of compensation effect, collection of status data after compensation;

[0220] S-e3, Effect Evaluation: Analyze the compensated state data and compare it with the target state. The root mean square error is used to evaluate the compensation effect, expressed as:

[0221]

[0222] Among them, D i It is the actual measurement data after compensation, D target,i The target data is N, which is the number of data points.

[0223] S-e4, Feedback Adjustment: Adjust compensation parameters and compensation instructions based on the results of the effect evaluation.

[0224] In this implementation, by performing the above-mentioned feedback steps, the compensation error is effectively reduced, the reliability and stability of the system are improved, thereby optimizing the overall compensation process and ensuring high-precision and high-efficiency operation.

[0225] In one implementation of this invention, the method by which the position calibration module calibrates the position of the aircraft connector may include the following steps:

[0226] S31, Obtain material and property data: Obtain material property data and spectral identification results for aircraft connectors;

[0227] S32, acquire thermal deformation compensation data;

[0228] S33, Position Calibration: Using the position calibration formula, the material and properties of the aircraft connectors, as well as thermal deformation compensation data, are used as inputs to calculate the calibration position P. cal , is represented as:

[0229] P cal =P measured +ΔP mat +ΔP therm ;

[0230] Among them, P cal For the calibrated aircraft connector positions, P measured For the original measurement position, ΔP mat For calibration quantities based on material and properties, ΔP therm This is a calibration amount based on thermal deformation;

[0231] ΔP mat =k mat ·(TT ref );

[0232] ΔP therm =k therm ·D;

[0233] Where, k mat Here is the material property calibration coefficient, and T is the actual temperature. ref For reference temperature, k therm Here, D is the thermal deformation compensation coefficient, and D is the thermal deformation compensation data.

[0234] S34, Perform position calibration: based on the calculated calibration position P cal Adjust the position of the aircraft connectors.

[0235] In this implementation method, the above-mentioned steps of calibrating the position of the aircraft connector are carried out. Taking into account the material properties and thermal deformation compensation data of the aircraft connector, the position of the connector can be precisely adjusted, thereby ensuring the accurate assembly and functional stability of the aircraft connector in the actual working environment.

[0236] This invention provides a spectral identification and position calibration system for aircraft connectors. On the one hand, by combining a spectral identification module with an adaptive noise filtering algorithm, the system can effectively remove the interference of environmental noise on spectral data, thereby improving the accuracy and reliability of spectral data. This process ensures the accurate identification of the material and characteristics of aircraft connectors, providing a solid data foundation for subsequent thermal deformation compensation and position calibration. The adaptive noise filtering algorithm has the ability to dynamically adjust the filtering coefficient, which can adapt to different noise environments in real time, further improving the accuracy of spectral identification.

[0237] On the other hand, by monitoring the temperature of the connectors in real time and combining thermodynamic modeling to accurately calculate thermal deformation at different temperatures, the system can generate effective compensation commands, including displacement, angle adjustment, stress release, etc., ensuring the accurate position and functional stability of the connectors under different temperature conditions. The feedback mechanism in the compensation process also optimizes the compensation effect, reduces errors, and improves the stability and reliability of the system through real-time monitoring and effect evaluation.

[0238] On the other hand, through comprehensive analysis of material properties and thermal deformation data, the system can achieve high-precision adjustment of connector positions, ensuring accurate assembly of connectors in actual working environments. This calibration process significantly improves the efficiency of aircraft maintenance and manufacturing, optimizes the assembly quality of aircraft connectors, and enhances the performance and safety of aircraft under various working conditions.

[0239] While the embodiments disclosed in this invention are as described above, they are merely illustrative of the embodiments to facilitate understanding of the invention and are not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and variations in the form and details of the implementation without departing from the spirit and scope disclosed herein; however, the scope of patent protection for this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A spectral identification and position calibration system for aircraft connectors, characterized in that, include: The system consists of a spectrum recognition module, an adaptive noise filtering module, a data processing module, a position calibration module, and a control and display module connected in sequence; a thermal deformation prediction and compensation module connected to the position calibration module; and multiple temperature sensors electrically connected to the thermal deformation prediction and compensation module. The spectral recognition module is used to acquire the spectral data of the aircraft connectors. The adaptive noise filtering module is used to remove environmental noise from the spectral data obtained by the spectral recognition module based on an adaptive noise filtering algorithm. The data processing module is used to identify the material and characteristics of aircraft connectors based on spectral data after removing environmental noise. The thermal deformation prediction and compensation module is used to predict the thermal deformation of the connector based on a thermodynamic model and real-time temperature monitoring data obtained by temperature sensors, and to perform real-time thermal deformation compensation for the aircraft connector; the processing method of the thermal deformation prediction and compensation module includes: Sa, Temperature Monitoring: The temperature of the aircraft connector is monitored in real time by multiple temperature sensors arranged on the aircraft connector. Sb, Thermodynamic Modeling: Establishing a thermodynamic model of the connector to predict its thermal deformation behavior under different temperature conditions; Sc, Real-time Analysis: Input the temperature of the aircraft connectors monitored in real time into the thermodynamic model to calculate the real-time thermal deformation. Sd, thermal deformation compensation: Generates compensation instructions based on the calculated thermal deformation amount; Se, Execution Feedback: Perform thermal deformation compensation according to the generated compensation instructions, and monitor the compensation effect in real time; The position calibration module is used to calibrate the position of the aircraft connector based on the identification results of the material and characteristics of the aircraft connector by the data processing module and the thermal deformation compensation results of the aircraft connector by the thermal deformation prediction and compensation module. The control and display module is used to execute the control calibration process of the aircraft connector and to display the spectral recognition results and position calibration results.

2. The spectral identification and position calibration system for aircraft connectors according to claim 1, characterized in that, The spectral recognition module includes: a light source unit, a spectral sensor, and a scanning unit; The light source unit is used to emit a light beam within a predetermined wavelength range onto the surface of the aircraft connector. The spectral sensor is used to receive light beams reflected or transmitted from the surface of the aircraft connector and convert them into spectral signals; The scanning unit is used to control the movement of the light source unit and the spectral sensor to perform a comprehensive spectral scan of the entire surface of the aircraft connector.

3. The spectral identification and position calibration system for aircraft connectors according to claim 1, characterized in that, The adaptive noise filtering module includes a noise sensor and an adaptive filter; the adaptive noise filtering module executes the adaptive noise filtering algorithm in the following ways: S11, Initialization: Set the initial filter coefficients w(0) to a zero vector, and the learning rate μ to a positive number, expressed as: w(0) = 0, μ > 0; S12, Noise monitoring: Record the environmental noise signal x(n) in real time using a noise sensor; S13, Spectral data recording: Record spectral data d(n) containing noise; S14, Noise Estimation: Estimate the noise signal by outputting an adaptive filter. Represented as: Where, w(n) T It is the transpose of the adaptive filter coefficient vector at the nth iteration time; S15, Error Signal Calculation: Calculate the difference between the actual spectral data and the estimated noise signal, expressed as: Where e(n) is the error signal at the nth iteration time; S16, Filter coefficient update: Update the filter coefficients w(n) according to the error signal, expressed as: w(n+1)=w(n)+vx(n)e(n); Where w(n+1) is the adaptive filter coefficient vector at the (n+1)th iteration, w(n) is the adaptive filter coefficient vector at the nth iteration, and μx(n)e(n) is the amount adjusted according to the current environmental noise signal and error signal.

4. The spectral identification and position calibration system for aircraft connectors according to claim 1, characterized in that, The data processing module's processing methods include: S21, Spectral data preprocessing: Normalize the spectral data after removing environmental noise; S22, Feature Extraction: Extract key features from the normalized spectral data, including peak position, peak intensity, and full width at half maximum (FWHM), expressed as: l peak =argmax λ d norm (l); I peak =max λ d norm (l); FWHM = λ2 - λ1; Where, λ peak It is the peak position, I peak It is the peak intensity, FWHM is the full width at half maximum (FWHM), λ is the wavelength, and d is the peak intensity. norm (λ) is the intensity value of the normalized spectral data at wavelength λ, and λ1 and λ2 are the spectral intensities that are half the peak intensity (I). peak The wavelength position corresponding to / 2); S23, Classification and Recognition: Use the support vector machine algorithm to classify the extracted key features and identify the material and characteristics of aircraft connectors.

5. The spectral identification and position calibration system for aircraft connectors according to claim 1, characterized in that, Multiple temperature sensors are pre-positioned at different locations on the aircraft connector; the thermal deformation prediction and compensation module performs temperature monitoring in the following ways: S-a1, Data Acquisition: Temperature data is periodically collected from each temperature sensor, represented as: T i (t)=T i (t); Among them, T i (t) is the temperature data recorded by the temperature sensor at position i at time t; S-a2, Temperature Data Analysis: The collected temperature data is analyzed to generate an overall temperature distribution map of the aircraft connectors, represented as follows: T dist =f(T1(t),T2(t),...,T n (t)); Among them, T dist This is the overall temperature distribution diagram of the connector, and f(·) is the temperature distribution calculation function.

6. The spectral identification and position calibration system for aircraft connectors according to claim 5, characterized in that, The thermodynamic model adopts a thermofluid dynamics model, and the thermodynamic modeling method performed by the thermal deformation prediction and compensation module includes: S-b1, initialization and mesh generation, includes: 3D modeling of the aircraft connectors and decomposing them into multiple finite volume elements using mesh generation techniques, represented as: Where Ω is the global domain of the connector, Ω i It is the i-th finite volume element, and N is the total number of elements; S-b2, establish the fluid motion equations, including: describing the flow behavior of the fluid on the surface of the aircraft connector, expressed as: Where u is the fluid velocity, p is the pressure, μ is the dynamic viscosity, and f is the body force; S-b3 establishes an energy equation to describe the heat transfer and temperature change between the fluid and the aircraft connection, expressed as: Where ρ is density, c p It is the specific heat capacity at constant pressure, T is the temperature, k is the thermal conductivity, and Q is the internal heat source; S-b4 establishes a solid thermal stress equation to describe the stress-strain relationship of aircraft connectors under temperature changes, expressed as: s ij =C ijkl (∈ kl -a kl ΔT); Where, σ ij It is the stress tensor, C ijkl It is the elastic modulus, ∈ kl It is the strain tensor, α kl ΔT is the coefficient of thermal expansion, and ΔT is the change in temperature. S-b5 sets interfacial coupling conditions for the solid thermal stress equation to describe the interfacial heat exchange and thermal stress transfer between the fluid and aircraft connectors, expressed as: q interface =h(T f -T s ); Where, q interface It is the interfacial heat flux, h is the convective heat transfer coefficient, and T is the interfacial heat flux. f It is the fluid temperature, T s It is the surface temperature of the solid; S-b6, Iterative solution: The numerical iterative method is used to solve the equations from S-b2 to S-b5 to obtain the temperature field and stress field of the fluid and aircraft connection parts; The temperature field is represented as: Among them, T n+1 It is the temperature field at the (n+1)th iteration, T n This is the temperature field at the nth iteration, where Δt is the time step, α is the thermal diffusivity, Q is the internal heat source, and u... n It is the fluid velocity at the nth iteration time; The stress field is represented as: in, It is the stress tensor at the (n+1)th iteration. It is the strain tensor at the (n+1)th iteration, α kl It is the coefficient of thermal expansion, ΔT n+1 It represents the temperature change at the (n+1)th iteration.

7. The spectral identification and position calibration system for aircraft connectors according to claim 6, characterized in that, The thermal deformation prediction and compensation module performs real-time analysis in the following ways: S-c1, Temperature Data Input: Input the temperature data {T} monitored by each temperature sensor. i (t)} is input into the thermodynamic model of the thermal fluid in real time; S-c2, Solving the thermodynamic model: Based on the input temperature data, the temperature field T(t) and stress field σ(t) of the aircraft connector are calculated using the thermodynamic model. S-c3, Calculation of thermal deformation: By solving for the temperature field and stress field, the real-time thermal deformation ΔL of the aircraft connector is calculated, expressed as: ΔL=αL0ΔT; Where ΔL is the length change, α is the coefficient of thermal expansion, L0 is the initial length, and ΔT is the temperature change.

8. The spectral identification and position calibration system for aircraft connectors according to claim 7, characterized in that, The thermal deformation prediction and compensation module performs thermal deformation compensation in the following ways: S-d1, Thermal Deformation Input: Receives the calculated thermal deformation ΔL; S-d2, Calculate compensation parameters: Calculate the required compensation parameters based on the thermal deformation, including displacement and angle adjustments, expressed as: C displacement =b displacement ΔL; Among them, C displacement β is the displacement compensation parameter. displacement ΔL is the displacement compensation coefficient, and ΔL is the thermal deformation. C angle =b angle ΔL; Among them, C angle β is the angle compensation parameter. angle ΔL is the angle compensation coefficient, and ΔL is the thermal deformation. S-d3, Compensation Command Generation: Compensation commands are generated based on compensation parameters and temperature monitoring results. These commands include position adjustment commands, angle adjustment commands, stress release commands, temperature control commands, and mechanical correction commands. The stress release commands are obtained by adjusting displacement and angle caused by thermal deformation and material property changes of aircraft connectors. The temperature control commands are generated based on real-time temperature monitoring results. The mechanical correction commands are obtained by physical correction of the overall mechanical system based on a comprehensive consideration of position, angle, stress, and temperature factors.

9. The spectral identification and position calibration system for aircraft connectors according to claim 8, characterized in that, The feedback methods implemented by the thermal deformation prediction and compensation module include: S-e1, Compensation Execution: Execute the actual compensation operation according to the compensation instruction; S-e2, Effect Monitoring: Real-time monitoring of compensation effect, collection of status data after compensation; S-e3, Effect Evaluation: Analyze the compensated state data and compare it with the target state. Use root mean square error to evaluate the compensation effect. S-e4, Feedback Adjustment: Adjust compensation parameters and compensation instructions based on the results of the effect evaluation.

10. The spectral identification and position calibration system for aircraft connectors according to claim 1, characterized in that, The position calibration module calibrates the position of the aircraft connectors in the following ways: S31, Obtain material and property data: Obtain material property data and spectral identification results for aircraft connectors; S32, acquire thermal deformation compensation data; S33, Position Calibration: Using the position calibration formula, the material and properties of the aircraft connectors, as well as thermal deformation compensation data, are used as inputs to calculate the calibration position P. cal , is represented as: P cal =P measured +ΔP mat +ΔP therm ; Among them, P cal For the calibrated aircraft connector positions, P measured For the original measurement position, ΔP mat For calibration quantities based on material and properties, ΔP therm This is a calibration value based on thermal deformation; ΔP mat =k mat ·(T-T ref ); ΔP therm =k therm ·D; Where, k mat Here is the material property calibration coefficient, and T is the actual temperature. ref For reference temperature, k therm Here, D is the thermal deformation compensation coefficient, and D is the thermal deformation compensation data. S34, Perform position calibration: based on the calculated calibration position P cal Adjust the position of the aircraft connectors.

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