Method and system for detecting icing on surface of airplane surface based on polarization component model

Abstract

The invention provides an airplane surface icing detection method and system based on a polarization component model, and relates to the technical field of complex refractive index measurement and polarization detection.The method comprises the steps that the complex refractive index is calculated through polarization degree image data of airplane surface icing, and skin complex refractive index data is obtained; inputting skin complex refractive index data into the polarization component model, and analyzing to obtain a light path polarization condition; and based on the light path polarization condition, analyzing the polarization degree image data to obtain an airplane surface icing detection result, and completing airplane surface icing detection. The method solves the problem that ice on the surface of an airplane is difficult to detect quickly, accurately and reliably and is easily influenced by light intensity.

Description

Technical Field

[0001] The present invention relates to the technical field of complex refractive index measurement and polarization detection, and in particular to a method and system for detecting ice accumulation on an aircraft surface based on a polarization component model. Background Art

[0002] Aircraft icing is one of the important factors leading to aircraft accidents and one of the six major meteorological factors affecting aircraft flight. Under icing conditions, ice accumulation on the aircraft surface not only increases the weight of the aircraft, but also seriously affects the aircraft's controllability and power performance, and even endangers flight safety. In addition, ice accumulation also seriously harms the sensors on the aircraft surface. When ice accumulates on the sensor surface, it will interfere with the sensor's detection data, thereby adversely affecting engine status detection and the pilot's judgment of flight parameters.

[0003] Current aircraft surface ice detection is still primarily based on human visual inspection, a method with low efficiency, uncertain accuracy, and vulnerability to environmental factors and the status of inspectors. The difference in surface optical properties between ice and aircraft skin is substantial, and detection based on this difference can significantly improve detection accuracy and efficiency compared to existing methods. Existing research on optical detection methods primarily includes infrared thermal imaging, reflectivity-based, and multispectral ice detection methods. However, these methods all have drawbacks. Infrared thermal imaging does not clearly differentiate between skin and ice under certain temperature conditions, reflectivity detection cannot be performed in dim conditions, and multispectral ice detection cannot cope with complex detection environments. The equipment is expensive and data processing time is lengthy. Summary of the Invention

[0004] In response to the above-mentioned deficiencies in the prior art, the present invention provides a method and system for detecting aircraft surface icing based on a polarization component model, which solves the problems of difficulty in detecting aircraft surface icing quickly, accurately and reliably and susceptibility to light intensity.

[0005] In order to achieve the above-mentioned object, the present invention adopts a technical solution: a method for detecting ice accumulation on an aircraft surface based on a polarization component model, comprising:

[0006] S1: Using the polarization image data of ice accumulation on the aircraft surface, the complex refractive index is calculated to obtain the complex refractive index data of the aircraft skin;

[0007] S2: Inputting the skin complex refractive index data into the polarization component model, and obtaining the polarization of the light path through analysis;

[0008] S3: Based on the polarization condition of the optical path, the polarization degree image data is analyzed to obtain an aircraft surface icing detection result, thereby completing the aircraft surface icing detection.

[0009] The beneficial effects of the present invention are as follows: a method for detecting ice accumulation on an aircraft surface based on a polarization component model uses polarization image data of ice accumulation on the aircraft surface to measure skin complex refractive index data; a polarization component model is constructed based on the skin complex refractive index data, and the optical path of light transmitted inside the ice accumulation and the polarization condition of each optical path are deduced according to the refraction and propagation laws of light; then, corresponding weighted parameters are measured according to the differences in surface and internal properties of ice accumulation of different ice types, and the parameters are introduced into the corresponding optical paths to obtain the polarization conditions of the optical paths of different ice accumulation types; based on the polarization component model and the polarization conditions of the optical paths of different ice accumulation types, a curve of the polarization degree of the skin and ice accumulation as a function of the incident angle can be deduced; and based on the parameters in the polarization curve, a polarization image measured by a polarization camera is judged to obtain the ice type and distribution of ice accumulation on the skin surface.

[0010] (1) It can quickly, accurately, reliably and not be affected by light intensity to perform optical inspection of ice accumulation on aircraft surfaces. (2) It can complete the inspection of the location, ice type and thickness of ice accumulation on the skin surface in complex and dim environments, realizing non-contact inspection. The main hardware system required is relatively simple, and the result is intuitive. Compared with the current inspection method, it improves the inspection quality, improves the inspection efficiency and is cost-controllable. (3) The inspection results are more stable, and the generation of the polarization curve of the metal skin surface is completed. The result is that the polarization image will not have a value exceeding the sensor reading limit; the implementation process is simpler, and only one set of complex refractive index measurements is required to support all subsequent inspection work; the polarization component model is established, and the type and thickness of ice accumulation can be detected; after completing the complex refractive index measurement, no external light source is required during the on-site inspection of ice accumulation on the aircraft surface, which is faster and more convenient.

[0011] Furthermore, the S1 includes:

[0012] Normalizing and averaging the spot positions of the polarization degree image data of ice accumulation on the aircraft surface to obtain polarization degree values at various angles;

[0013] Based on the angle value and the corresponding polarization degree value, the skin complex refractive index data is obtained by calculation:

[0014]

[0015] in, It represents the polarization degree of the light reflected from the surface of the object measured by the sensor in group j, p jThe original polarization degree expression with n and k as independent variables represents the theoretical value of the polarization degree before Taylor expansion simplification under the measurement conditions of the jth group, Δn represents the offset of the real part of the complex refractive index to be measured relative to the real part value of the reference point, Δk represents the offset of the imaginary part of the complex refractive index to be measured relative to the imaginary part value of the reference point, a represents the real part value of the reference point, b represents the imaginary part value of the reference point, n represents the real part of the complex refractive index, and k represents the imaginary part of the complex refractive index. Among them, the polarization degree of the reflected light from the object surface measured by the sensor in the jth group belongs to the skin complex refractive index data.

[0016] Furthermore, the S2 includes:

[0017] Inputting the skin complex refractive index data into a polarization component model to obtain a reflection coefficient of a vertical polarization component and a reflection coefficient of a horizontal polarization component;

[0018] Based on the reflection coefficient of the vertical polarization component and the reflection coefficient of the horizontal polarization component, the polarization condition of the light path is obtained through calculation.

[0019] Furthermore, the expression of the polarization component model is:

[0020]

[0021] Where n1 represents the complex refractive index of the incident material, n2 represents the complex refractive index of the incident material, θ i represents the incident angle at time i, R s Indicates the reflectivity of polarized light in the vertical direction, R p Indicates the reflectivity of polarized light in the parallel direction.

[0022] Furthermore, the expression of the polarization condition of the optical path is:

[0023]

[0024] Wherein, P represents the degree of polarization measured according to the polarization component model.

[0025] Furthermore, the S3 includes:

[0026] The polarization condition of the optical path shows that the polarization image is darker than the metal skin, which is the thinner ice.

[0027] The polarization condition of the optical path shows that the polarization image is slightly brighter than the metal skin part, which is used as the detection of clear ice, thick clear ice, hairy ice, rime and frost at large angles;

[0028] The polarization condition of the optical path shows that the completely black part of the polarization image is snow accumulation, completing the detection of icing on the aircraft surface; among them, thin ice, ice detected at a large angle, thick ice, hairy ice, rime, frost and snow are all included in the aircraft surface icing detection results.

[0029] The present invention also provides an aircraft surface ice accumulation detection system based on a polarization component model, comprising:

[0030] an acquisition module, configured to calculate the complex refractive index using the polarization degree image data of ice accumulation on the aircraft surface, and obtain the complex refractive index data of the skin; wherein the polarization degree image data of ice accumulation on the aircraft surface is obtained by an image acquisition device;

[0031] An analysis module, configured to input the skin complex refractive index data into a polarization component model and obtain the polarization of the light path through analysis;

[0032] The detection module is used to analyze the polarization degree image data based on the polarization condition of the optical path, obtain the aircraft surface icing detection result, and complete the detection of aircraft surface icing.

[0033] Furthermore, the image acquisition device includes:

[0034] Height-adjustable horizontal angle bracket for fixing the sample of ice accumulation on the aircraft surface;

[0035] LED light source, used as the light source for the sample being tested;

[0036] A polarization camera, used to obtain an initial polarization image of the sample under test;

[0037] The computer is used to process the initial polarization image to obtain polarization image data of ice accumulation on the aircraft surface. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] This specification will be further described in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, like numbers represent like structures, wherein:

[0039] Figure 1 is a module schematic diagram of an aircraft surface ice accumulation detection system based on a polarization component model according to some embodiments of this specification;

[0040] Figure 2 This is an exemplary flow chart of aircraft surface ice accumulation detection based on a polarization component model according to some embodiments of this specification. DETAILED DESCRIPTION

[0041] The specific embodiments of the present invention are described below to facilitate understanding of the present invention by those skilled in the art. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the appended claims, these changes are obvious, and all inventions and creations utilizing the concepts of the present invention are protected.

[0042] Example 1

[0043] Figure 1 This is a module diagram of an aircraft surface ice accumulation detection system based on a polarization component model according to some embodiments of this specification.

[0044] In some embodiments, the aircraft surface ice accumulation detection system based on the polarization component model may include an acquisition module, an analysis module, and a detection module.

[0045] The acquisition module is used to calculate the complex refractive index using the polarization degree image data of ice accumulation on the aircraft surface to obtain the complex refractive index data of the skin; wherein the polarization degree image data of ice accumulation on the aircraft surface is obtained by an image acquisition device.

[0046] In some embodiments, the image acquisition device may include: a height-adjustable horizontal angle bracket for fixing the sample to be tested of ice accumulation on the aircraft surface; an LED light source for serving as the light source of the sample to be tested; a polarization camera for acquiring an initial polarization image of the sample to be tested; and a computer for processing the initial polarization image to obtain polarization image data of ice accumulation on the aircraft surface; wherein the height-adjustable horizontal angle bracket includes a first height-adjustable horizontal angle bracket and a second height-adjustable horizontal angle bracket.

[0047] In some embodiments, the polarization camera 3 uses the Hikvision Robotics MV-CH050-10UP high-end polarization camera, which uses Sony's IMX250MZR polarization sensor chip. The sensor is equipped with a four-directional (0°, 45°, 90°, 135°) pixel-level polarization filter, which can capture different degrees of polarization information in the object in the picture and calculate the corresponding polarization degree image in real time.

[0048] In some embodiments, a first height-adjustable horizontal angle bracket and a second height-adjustable horizontal angle bracket are fixed to an optical panel. The skin sample to be measured is vertically arranged on the central axis of the line connecting the first height-adjustable horizontal angle bracket and the second height-adjustable horizontal angle bracket, and the direction is parallel to the direction of the line connecting the two brackets. The polarization camera and LED light source are placed on the brackets at a certain angle. The polarization camera and LED light source are at the same height, and the incident and receiving angles are equal. During the measurement process, the polarization camera and LED light source remain fixed. After the aperture of the LED light source is adjusted, the light emitted is parallel to the direction of light propagation. After the aperture and focal length of the polarization camera lens are adjusted, a polarization image of the skin surface can be captured without overexposure. The computer uses an image processing module to process the polarization image of the skin surface, completing the acquisition of polarization image data of the aircraft skin at a certain angle.

[0049] In some embodiments, a polarization camera is placed on a first height-adjustable horizontal angle bracket, an LED light source is placed on an opposite second height-adjustable horizontal angle bracket, and a test skin sample is placed between the two. The distance and angle between the polarization camera and the LED light source are adjusted to keep the three in a straight line and the distances between the two brackets and the skin equal. The incident angle of the LED light source on the skin sample is kept equal to the receiving angle of the polarization camera, and it is ensured that the polarization camera can receive the light spot on the skin sample. Then, the light input and focal length parameters of the polarization camera are adjusted to a position where the image is clear and not overexposed, and the first picture is taken. The polarization camera and the LED light source are adjusted to a new distance and angle with a significant change, keeping the three in a straight line and the distances between the two brackets and the skin equal. The incident angle of the LED light source on the skin sample is kept equal to the receiving angle of the polarization camera, and it is ensured that the polarization camera can receive the light spot on the skin sample. Then, the light input and focal length parameters of the polarization camera are adjusted to a position where the image is clear and not overexposed, and the next picture is taken. All pictures are combined to obtain polarization image data of ice accumulation on the aircraft surface.

[0050] The analysis module is used to input the skin complex refractive index data into the polarization component model, and obtain the polarization condition of the light path through analysis.

[0051] The detection module is used to analyze the polarization degree image data based on the polarization condition of the optical path, obtain the aircraft surface icing detection result, and complete the detection of aircraft surface icing.

[0052] In some embodiments, a system for detecting icing on an aircraft surface based on a polarization component model may be used to perform a method for detecting icing on an aircraft surface based on a polarization component model.

[0053] In some embodiments of the present specification, the processor uses an aircraft surface ice detection system based on a polarization component model to execute an aircraft surface ice detection method based on a polarization component model. In this way, (1) optical detection of aircraft surface ice can be performed quickly, accurately, reliably, and not easily affected by light intensity. (2) The position, ice type, and thickness of ice on the skin surface can be detected in a complex and dim environment, achieving non-contact detection. The required main hardware system is relatively simple, and the result is intuitive. Compared with the current detection method, the detection quality is improved, the detection efficiency is increased, and the cost is controllable. (3) The detection result is more stable, and the generation of the polarization curve of the metal skin surface is completed. The result is that the polarization image will not have a value exceeding the sensor reading limit; the implementation process is simpler, and only one set of complex refractive index measurements is required to support all subsequent detection work; the establishment of the ice accumulation optical model is completed, and the type and thickness of ice accumulation can be detected; after completing the complex refractive index measurement, no external light source is required during the on-site detection stage of aircraft surface ice accumulation, which is faster and more convenient.

[0054] Example 2

[0055] Figure 2 This is an exemplary flow chart of a method for detecting ice accumulation on an aircraft surface based on a polarization component model according to some embodiments of this specification. Figure 2 As shown, the process includes the following steps. In some embodiments, the process can be executed by a processor.

[0056] S1: Using the polarization image data of ice accumulation on the aircraft surface, the complex refractive index is calculated to obtain the complex refractive index data of the aircraft skin.

[0057] Polarization image data is data reflecting polarization information of images at different angles.

[0058] The skin complex refractive index data is data reflecting the complex refractive index information of the aircraft surface skin.

[0059] In some embodiments, the processor can implement S1 based on the following steps: normalizing and averaging the spot position of the polarization image data of ice accumulation on the aircraft surface to obtain polarization values at various angles; and obtaining skin complex refractive index data through calculation based on the angle values and corresponding polarization values.

[0060] The polarization degree value is the normalized value of the polarization degree at each spot position.

[0061] In some embodiments, the processor can introduce the Stokes vector to calculate the skin complex refraction: Stokes vector S = [IQ UV] T is generally used to describe the polarization information of light, where I represents the total light intensity, Q represents the light intensity difference between the horizontal and vertical (0° and 90°) polarization directions, and U represents the light intensity difference between the two polarization directions of 45° and 135°. V represents the light intensity difference between left-handed and right-handed circularly polarized light. Natural light and white LED light can be measured and represented by [1 0 0 0] T. At the same time, the influence of the rotation of polarized light on the results during detection by the polarization camera can be ignored. Therefore, Stokes vector S = [IQ U] T is selected, and natural light and white LED light are represented by [1 0 0] T. The degree of polarization (P) of this light beam is reflected by the formula:

[0062]

[0063] Where P represents the degree of polarization measured according to the polarization component model, Q represents the light intensity difference between the horizontal and vertical polarization directions, U represents the light intensity difference between the 45° and 135° polarization directions, and I represents the total light intensity.

[0064] By comparing the two light intensity data as the calculation result, the polarization degree is not affected by the intensity of the incident light.

[0065] In some embodiments, the complex refractive index of a substance may be expressed as:

[0066]

[0067] in, represents the complex refractive index of the material, n represents the real part of the complex refractive index, k represents the imaginary part of the complex refractive index, and j1 represents the imaginary unit.

[0068] In some embodiments, the processor may derive an expression for the Fresnel equation for polarized light based on the law of refraction and Maxwell's equations:

[0069]

[0070] Among them, Rs represents the reflectivity of polarized light in the vertical direction, Rp represents the reflectivity of polarized light in the parallel direction, n1 represents the complex refractive index of the incident material, n2 represents the complex refractive index of the reflecting material, θ i represents the angle of incidence at time i; where:

[0071] R s =|r s | 2 R p =|r p | 2 ;

[0072]

[0073] Among them, r s and r p Represent the reflection coefficients of Rs and Rp respectively.

[0074] The reflection coefficient is the ratio of the reflected wave to the incident wave.

[0075] In most cases, the vertical polarization component of the light reflected from the metal skin is greater than the horizontal polarization component, but the difference between the two polarization components is very small except near the Brewster angle, which leads to a smaller polarization degree of the metal in most cases.

[0076] In some embodiments, to obtain the accurate complex refractive index of the metal skin, the processor may further transform the Fresnel formula into:

[0077]

[0078] Where A and B are functions of C and D, and β represents the mean of the incident angle and the reflection angle. The expressions of A and B can be:

[0079]

[0080] Where C represents a function of n, k, and D, D represents a function of n, k, and β, θ1 represents the incident angle, θ2 represents the reflection angle, and θ AC represents the sum of the angle of incidence and the angle of reflection.

[0081] In some embodiments, the incident angle and the reflection angle selected in the test step may be equal, that is, β=θ1=θ2.

[0082] In some embodiments, the values of C and D are related to the values of n and k: C = 4n 2 k 2 +D 2 , D=n 2 -k 2 -sin 2 (β); where k represents the imaginary part of the complex refractive index.

[0083] In some embodiments, since the phase of the light generated by the LED light source is completely random, the 45° and 135° polarized light received by the polarization camera are almost completely equal, that is, the Stokes vector U is almost zero. Therefore, the processor can simplify the polarization degree measurement formula to: Then, the new polarization degree expression is:

[0084]

[0085] Among them, pj The original polarization degree expression with n and k as independent variables represents the theoretical value of the polarization degree before Taylor expansion simplification under the measurement conditions of the jth group, A j represents the value of A under this set of experimental conditions, B j represents the value of B under this set of experimental conditions, β j Represents the incident angle, and j represents the number of measurement groups.

[0086] In some embodiments of the present invention, the efficiency of the calculation process also needs to be considered. Polynomials are more advantageous than complex fractions in solving equations. At the same time, since the n and k parameters of the skin tested in the present invention vary slightly with wavelength under visible light, the method adopted by the present invention is to perform Taylor expansion replacement on Pj(n,k) at point (a,b) to simplify the complexity of the formula. The point (a,b) should be selected from the database data of n and k of the material under the test wavelength. Specifically, the processor can take E j =sin 2 (β), then cos 2 (β)=1-E j , and since β∈(0,π / 2), The polarization degree expression can be transformed into:

[0087]

[0088] Among them, E j represents the value of E measured under the jth set of experimental conditions, where E = sin 2 (β), β represents the average value of the incident angle and the reflection angle. The expression for the degree of polarization is:

[0089]

[0090] Among them, F j represents the value of F under the experimental conditions of the jth group, and F represents the function of E G j represents the value of F under the experimental conditions of the jth group, and G represents the function of E E represents the square of the sine value of the average value of the incident angle and the reflection angle, j represents the number of measurement groups, j∈{1, 2,…, T}, and by changing the angle β after each measurement, a group of T equations can be obtained. After solving the equations, the aircraft skin n and k can be solved.

[0091] In some embodiments, since the present invention is to detect ice accumulation on the skin, the parameters of the skin and ice accumulation differ significantly, and the expansion points (a, b) selected by the present invention differ relatively little from n and k of the metal skin itself, the present invention uses the expansion mode of Taylor's second-order expansion to meet the parameter solution requirements. Then, the expression of the polarization degree can be further transformed into a polynomial that is simpler for solving the system of equations and more helpful in improving the accuracy of solving the system of equations.

[0092] In some embodiments, the expression for the skin complex refractive index data may be:

[0093]

[0094] in, It represents the polarization degree of the light reflected from the surface of the object measured by the sensor in group j, p j The original polarization degree expression with n and k as independent variables represents the theoretical value of the polarization degree before Taylor expansion simplification under the measurement conditions of the jth group, Δn represents the offset of the real part of the complex refractive index to be measured relative to the real part value of the reference point, Δk represents the offset of the imaginary part of the complex refractive index to be measured relative to the imaginary part value of the reference point, a represents the real part value of the reference point, b represents the imaginary part value of the reference point, n represents the real part of the complex refractive index, and k represents the imaginary part of the complex refractive index. Among them, the polarization degree of the reflected light from the object surface measured by the sensor in the jth group belongs to the skin complex refractive index data.

[0095] In some embodiments, the polarization degree of the light reflected from the object surface measured by the sensor in the jth group It can be used to measure and derive parameters of the complex refractive index of the skin.

[0096] In some embodiments, the parameters of the expression of the skin complex refractive index data may specifically be:

[0097] Δn=na,Δk=kb;

[0098]

[0099] Where F represents the function of E G represents the function of E E represents the square of the sine value of the average value of the incident angle and the reflection angle, M′1 represents the derivative of the intermediate variable function M1 with respect to n, in which the second-order partial derivative of P with respect to n is located in the numerator, N1 represents the intermediate variable function with respect to n, in which the second-order partial derivative of P with respect to n is located in the denominator, M1 represents the intermediate variable function with respect to n, in which the second-order partial derivative of P with respect to n is located in the numerator, M′2 represents the derivative of the intermediate variable function M2 with respect to k, in which the second-order partial derivative of P with respect to k is located in the denominator, and M2 represents the intermediate variable function with respect to k, in which the second-order partial derivative of P with respect to k is located in the numerator; wherein:

[0100]

[0101] Wherein, N3 represents the intermediate variable function with the second-order partial derivatives of P with respect to n and k located in the denominator, and M3 represents the intermediate variable function with the second-order partial derivatives of P with respect to n and k located in the numerator; where:

[0102]

[0103] In some embodiments, the expressions corresponding to A and B are:

[0104]

[0105] ξ1=(n 2 +k 2 -E+X1)[(4k 2 +2(n 2 -k 2 -E))Y1-2n 2 (4k 2 +2(n 2 -k 2 -E))]-4n 2 (4k 2 +2(n 2 -k 2 -E))X1;

[0106] Where ξ1 represents the numerator of the second-order partial derivative of A with respect to n, W1 represents the intermediate variable function with respect to n, k, and E, Y1 represents the intermediate variable function with respect to X, n, k, and E, and X1 represents the square root of W1; where:

[0107] W1=4n 2 k 2 +(n 2 -k 2 -E) 2 , Y1=X1+n 2 -k 2 -E;

[0108]

[0109] ξ2=(Z2-X2)[(2k 2 -2(n 2 -k 2 -E))Y2-4k 2 X2]-4k 2 (Z2-X2) 2 ;

[0110] Where ξ2 represents the numerator of the second-order partial derivative of A with respect to k, W2 represents the intermediate variable function with respect to n, k, and E, Y2 represents the intermediate variable function with respect to X, n, k, and E, X2 represents the square root of W2, and Z2 represents the intermediate variable function with respect to n, k, and E; where:

[0111] W2=4n 2 k 2 +(n 2 -k 2 -E) 2 , Y2=X2+n 2 -k 2 -E, Z2=n 2 +k 2 +E;

[0112]

[0113] Where ξ3 represents the numerator of the second-order partial derivative of A with respect to n and k, W3 represents the intermediate variable function with respect to n, k, and E, Y3 represents the intermediate variable function with respect to X, n, k, and E, X3 represents the square root of W3, and Z3 represents the intermediate variable function with respect to n, k, and E; where:

[0114] W3=4n 2 k 2 +(n 2 -k 2 -E) 2 , Y3=X3+n 2 -k 2 -E, Z3=n 2 +k 2 +E;

[0115]

[0116] ξ4=(Z4-X4)[(4k 2 +2(n 2 -k 2 -E))Y4-2n 2 (4k 2 +2(n 2 -k 2 -E))]-4n 2 (4k 2 +2(n 2 -k 2 -E))X4;

[0117] Where ξ4 represents the numerator of the second-order partial derivative of B with respect to n, W4 represents the intermediate variable function with respect to n, k, and E, Y4 represents the intermediate variable function with respect to X, n, k, and E, X4 represents the square root of W4, and Z4 represents the intermediate variable function with respect to n, k, and E; where:

[0118] W4=4n 2 k 2 +(n 2 -k 2 -E) 2 , Y4=X4-(n 2 -k 2 -E), Z4=n 2 +k 2 -E;

[0119]

[0120] Where ξ5 represents the numerator of the second-order partial derivative of B with respect to k, W5 represents the intermediate variable function with respect to n, k, and E, Y5 represents the intermediate variable function with respect to X, n, k, and E, X5 represents the square root of W5, and Z5 represents the intermediate variable function with respect to n, k, and E; where:

[0121] W5=4n 2 k 2 +(n 2 -k 2 -E) 2 , Y5=X5-(n 2 -k 2 -E), Z5=n 2 +k 2 +E;

[0122]

[0123] Where ξ6 represents the numerator of the second-order partial derivative of B with respect to n and k, W6 represents the intermediate variable function with respect to n, k, and E, Y6 represents the intermediate variable function with respect to X, n, k, and E, X6 represents the square root of W6, and Z6 represents the intermediate variable function with respect to n, k, and E; where:

[0124] W6=4n 2 k 2 +(n 2 -k 2 -E) 2 , Y6=X6-(n 2 -k 2 -E), Z6=n 2 +k2 -E.

[0125] In some embodiments, the processor can select the expansion point (a, b) as the database value (1.0152, 6.6273) of aluminum at a wavelength of 550nm, and select the normalized values in the area of 948 to 1065 horizontally and 801 to 930 vertically under the condition of 35 degrees to take the average value to obtain the polarization degree of the light spot at 35 degrees as 0.502. Under the condition of 50 degrees, the processor can select the normalized values in the area of 848 to 957 horizontally and 1004 to 1092 vertically to take the average value to obtain the polarization degree of the light spot at 50 degrees as 0.1175. Finally, the solution is n = 1.1751, k = 16.4210.

[0126] S2: Input the skin complex refractive index data into the polarization component model, and obtain the polarization of the light path through analysis.

[0127] The polarization component model is a mathematical model of the optical polarization condition used to calculate the polarization degree image data.

[0128] The optical path polarization condition is data reflecting the optical path polarization condition at each light spot position.

[0129] In some embodiments, the processor can implement S2 based on the following steps: inputting the skin complex refractive index data into the polarization component model to obtain the reflection coefficient of the vertical polarization component and the reflection coefficient of the horizontal polarization component; based on the reflection coefficient of the vertical polarization component and the reflection coefficient of the horizontal polarization component, obtaining the polarization condition of the optical path through calculation.

[0130] In some embodiments, the expression of the polarization component model may be:

[0131]

[0132] Where n1 represents the complex refractive index of the incident material, n2 represents the complex refractive index of the incident material, θ i represents the incident angle at time i, R s Indicates the reflectivity of polarized light in the vertical direction, R p Indicates the reflectivity of polarized light in the parallel direction.

[0133] In some embodiments, the expression of the optical path polarization condition may be:

[0134]

[0135] Wherein, P represents the degree of polarization measured according to the polarization component model.

[0136] S3: Based on the polarization condition of the optical path, the polarization degree image data is analyzed to obtain an aircraft surface icing detection result, thereby completing the aircraft surface icing detection.

[0137] The aircraft surface icing detection results reflect the ice accumulation detection results of various parts of the aircraft surface. For example, the aircraft surface icing detection results may include thin ice, ice detected at high angles, thick ice, fine ice, rime, frost, and snow.

[0138] In some embodiments, the processor can implement S3 based on the following steps: the optical path polarization condition shows that the polarization image is darker than the metal skin, which is regarded as thinner clear ice; the optical path polarization condition shows that the polarization image is slightly brighter than the metal skin, which is regarded as clear ice, thick clear ice, hairy ice, rime and frost detected at a large angle; the optical path polarization condition shows that the polarization image is completely black, which is regarded as accumulated snow, thereby completing the detection of ice accumulation on the aircraft surface.

[0139] In some embodiments, the processor can, based on the attenuation characteristics of light propagating within a medium, determine that if light entering the medium is completely attenuated during propagation, its impact on the light received by the polarization camera need not be considered. If light is not completely attenuated, the reflectivity of the horizontal and vertical polarization components at the skin-ice interface and the ice-air interface, respectively, is calculated using the Fresnel equations to generate curves for the horizontal and vertical polarization components of the light emerging from the medium. Based on the superposition properties of light and the fact that the polarization components of natural light are completely equal in all directions and have random relative phases, the light reflected from the ice surface received by the polarization camera is a superposition of the aforementioned two light components. By analyzing the surface and internal characteristics of ice of different ice types and thicknesses, the variation in polarization characteristics of ice of different ice types and thicknesses with the angle of incident / received light can be determined, and the corresponding polarization degree curves can be calculated.

[0140] In some embodiments, the optical path identified by the processor is: the reflection at the interface is the same as the previous state, but the refracted light will produce a certain attenuation: R′ s =σR s , R′ p =σR p , where the value of σ decreases with the increase of angle and thickness, ranging from 1 to 0. The polarization distribution and polarization degree in both directions at each stage are as follows: when the angle is large or the thickness of the clear ice is large, the optical path of the light inside the ice is long, and the attenuation of the light inside the ice gradually increases, which is the clear ice state.

[0141] In some embodiments, the optical path identified by the processor is: the reflection at the interface will produce a certain attenuation: R' s =σR s , R′ p =σR p, where the value of σ decreases with the increase of roughness, ranging from 1 to 0. The polarization distribution and polarization degree in both directions at each stage are slightly attenuated, but can still support detection work. These are the states of shaggy ice, rime, and frost. The surfaces of these three types of ice are rough, and there are a large number of cavities, bubbles, and pore structures inside. Light will decay rapidly after entering, so the received light is mainly reflected from the ice surface.

[0142] In some embodiments, the light path identified by the processor is: when the reflectivity of the polarization in the two directions is equal and the polarization degree is zero, it is a snow accumulation state. Due to the complex porous structure of the surface and interior of the snow, the light will hardly undergo mirror reflection after it hits its surface. The light received at the polarization camera is diffusely reflected light produced by multiple reflections and refractions, and the difference in its polarization in the two directions is almost completely eliminated.

[0143] In some embodiments of the present specification, a method for detecting aircraft surface ice accumulation based on a polarization component model is provided. Polarization degree image data of aircraft surface ice accumulation is used to measure skin complex refractive index data. A polarization component model is constructed based on the skin complex refractive index data. The optical paths of light propagating within the ice accumulation and the polarization conditions of each optical path are derived based on the laws of light refraction and propagation. Subsequently, corresponding weighting parameters are measured based on differences in surface and internal properties of different ice types, and the parameters are substituted into the corresponding optical paths to obtain the polarization conditions of the optical paths for different ice types. Based on the polarization component model and the polarization conditions of the optical paths for different ice types, a curve of the polarization degree of the skin and ice accumulation as a function of the incident angle is derived. A polarization degree image measured using a polarization camera is then judged based on the parameters in the polarization degree curve to determine the ice type and distribution on the skin surface.

[0144] (1) It can conduct optical inspection of ice accumulation on aircraft surfaces quickly, accurately, reliably, and not be affected by light intensity. (2) It can complete the inspection of the position, ice type, and thickness of ice accumulation on the skin surface in complex and dim environments, realizing non-contact inspection. The required main hardware system is relatively simple, and the result is intuitive. Compared with the current inspection method, it improves the inspection quality, improves the inspection efficiency, and is cost-controlled. (3) The inspection results are more stable, and the generation of the polarization curve of the metal skin surface is completed. The result is that the polarization image will not have a value exceeding the sensor reading limit; the implementation process is simpler, and only one set of complex refractive index measurements is required to support all subsequent inspection work; the establishment of the ice accumulation optical model is completed, and the type and thickness of ice accumulation can be detected; after completing the complex refractive index measurement, no external light source is required during the on-site inspection of ice accumulation on the aircraft surface, which is faster and more convenient.

Claims

1. A method for detecting ice accumulation on an aircraft surface based on a polarization component model, characterized in that: include: S1: Using the polarization image data of ice accumulation on the aircraft surface, the complex refractive index is calculated to obtain the complex refractive index data of the aircraft skin; S2: Inputting the skin complex refractive index data into the polarization component model, and obtaining the polarization of the light path through analysis; S3: Based on the polarization condition of the optical path, the polarization degree image data is analyzed to obtain an aircraft surface icing detection result, thereby completing the aircraft surface icing detection.

2. The method for detecting ice accumulation on an aircraft surface based on a polarization component model according to claim 1, wherein: Said S1 comprises: Normalizing and averaging the spot positions of the polarization degree image data of ice accumulation on the aircraft surface to obtain polarization degree values at various angles; Based on the angle value and the corresponding polarization degree value, the skin complex refractive index data is obtained by calculation: in, It represents the polarization degree of the light reflected from the surface of the object measured by the sensor in group j, p j The original polarization degree expression with n and k as independent variables represents the theoretical value of the polarization degree before Taylor expansion simplification under the measurement conditions of the jth group, Δn represents the offset of the real part of the complex refractive index to be measured relative to the real part value of the reference point, Δk represents the offset of the imaginary part of the complex refractive index to be measured relative to the imaginary part value of the reference point, a represents the real part value of the reference point, b represents the imaginary part value of the reference point, n represents the real part of the complex refractive index, and k represents the imaginary part of the complex refractive index. Among them, the polarization degree of the reflected light from the object surface measured by the sensor in the jth group belongs to the skin complex refractive index data.

3. The method for detecting ice accumulation on an aircraft surface based on a polarization component model according to claim 1, wherein: The S2 includes: Inputting the skin complex refractive index data into a polarization component model to obtain a reflection coefficient of a vertical polarization component and a reflection coefficient of a horizontal polarization component; Based on the reflection coefficient of the vertical polarization component and the reflection coefficient of the horizontal polarization component, the polarization condition of the light path is obtained through calculation.

4. The method for detecting ice accumulation on an aircraft surface based on a polarization component model according to claim 3, wherein: The expression of the polarization component model is: Where n1 represents the complex refractive index of the incident material, n2 represents the complex refractive index of the incident material, θ i represents the incident angle at time i, R s Indicates the reflectivity of polarized light in the vertical direction, R p Indicates the reflectivity of polarized light in the parallel direction.

5. The method for detecting ice accumulation on an aircraft surface based on a polarization component model according to claim 4, characterized in that: The expression of the polarization of the optical path is: Wherein, P represents the degree of polarization measured according to the polarization component model.

6. The method for detecting ice accumulation on an aircraft surface based on a polarization component model according to claim 1, wherein: The S3 includes: The polarization condition of the optical path shows that the polarization image is darker than the metal skin, which is the thinner ice. The polarization condition of the optical path shows that the polarization image is slightly brighter than the metal skin part, which is used as the detection of clear ice, thick clear ice, hairy ice, rime and frost at large angles; The polarization condition of the optical path shows that the completely black part of the polarization image is snow accumulation, completing the detection of icing on the aircraft surface; among them, thin ice, ice detected at a large angle, thick ice, hairy ice, rime, frost and snow are all included in the aircraft surface icing detection results.

7. An aircraft surface icing detection system based on a polarization component model, configured to execute the aircraft surface icing detection method based on a polarization component model according to any one of claims 1 to 6, characterized in that: include: an acquisition module, configured to calculate the complex refractive index using the polarization degree image data of ice accumulation on the aircraft surface, and obtain the complex refractive index data of the skin; wherein the polarization degree image data of ice accumulation on the aircraft surface is obtained by an image acquisition device; An analysis module, configured to input the skin complex refractive index data into a polarization component model and obtain the polarization of the light path through analysis; The detection module is used to analyze the polarization degree image data based on the polarization condition of the optical path, obtain the aircraft surface icing detection result, and complete the detection of aircraft surface icing.

8. The aircraft surface ice detection system based on the polarization component model according to claim 7, characterized in that: The image acquisition device comprises: Height-adjustable horizontal angle bracket for fixing the sample of ice accumulation on the aircraft surface; LED light source, used as the light source for the sample being tested; A polarization camera, used to obtain an initial polarization image of the sample under test; The computer is used to process the initial polarization image to obtain polarization image data of ice accumulation on the aircraft surface.

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