Airport runway pavement black ice detection method based on multispectral imaging

Abstract

The invention discloses an airport runway pavement black ice detection method based on multispectral imaging. The method comprises the following steps: establishing an airport runway pavement black ice detection system based on multispectral imaging; obtaining a plurality of different asphalt pavement samples and irradiance spectrograms under different wavelengths in a visible light spectrum range; calculating the irradiance average value of the ponding, dry and black ice asphalt pavement samples and the white board under each wavelength; the corresponding relative irradiance is calculated; the relative irradiance of the to-be-measured asphalt pavement is obtained; and judging the state of the to-be-detected asphalt pavement, and the like. The method has the advantages that irradiance data in different asphalt pavement states can be processed through non-contact multispectral analysis, so that classified detection of the different asphalt pavement states is achieved, the accuracy and reliability of black ice detection are remarkably improved, safety accidents caused by black ice on airport runways can be effectively prevented, and the method is suitable for popularization and application. And the method has important engineering application value.

Description

Technical Field

[0001] The present invention belongs to the technical field of airport runway pavement status detection, and in particular relates to a method for detecting black ice on airport runway pavements based on multispectral imaging. Background Art

[0002] Among the major road traffic accidents in my country, the impact of inclement weather, such as rain, snow, and ice, is particularly pronounced. Airport runways, as essential infrastructure for aircraft takeoff and landing, are significantly impacted by inclement weather, posing a direct threat to aircraft safety and operational efficiency. Rain, snow, and ice reduce the friction coefficient of the runway surface, increasing braking distances. Of all road traffic issues, black ice poses the greatest potential for accidents. Black ice is a thin layer of frozen ice on the road surface. Because it resembles the color of asphalt or concrete runways, it is difficult to detect with the naked eye, posing a serious threat to aircraft takeoff and landing and ground operations. Due to the difficulty of road surface detection, black ice has been identified as a major cause of traffic accidents. Therefore, providing users with early warnings of black ice is crucial. The threat posed by black ice to airport runways lies in its concealed nature and slippery, low-friction properties, which significantly reduce the adhesion between aircraft tires and the ground. During taxiing or takeoff, black ice can cause the rear wheels to skid, potentially leading to runway deviation and aircraft spin. Black ice appears wet under illumination, making it difficult for pilots to visually detect, requiring them to rely on sensors for assistance.

[0003] At present, the technical means for monitoring road conditions and detecting black ice are not mature enough. Current methods for detecting black ice on road surfaces include contact and non-contact sensor detection methods. For the contact sensor detection method, it uses the resistance change between stainless steel inside the concrete to detect the road surface condition. The disadvantage of this method is that it is large in engineering effort and high in cost. For the non-contact sensor detection method, it is carried out under reflective and diffuse reflection environmental conditions using a detector consisting of an optical sensor and an infrared thermometer. However, for asphalt pavement, ice particles will be embedded in the gaps of the pavement material, causing small changes in the scattering coefficient and refractive index of the pavement. Therefore, it is necessary to design a method for detecting black ice on airport runway pavements to solve the above technical problems. Summary of the Invention

[0004] In order to solve the above problems, the purpose of the present invention is to provide a method for detecting black ice on airport runway pavement based on multispectral imaging.

[0005] To achieve the above objectives, the present invention provides a method for detecting black ice on airport runway pavement based on multispectral imaging, comprising the following steps performed in sequence:

[0006] 1) Establish an airport runway pavement black ice detection system based on multispectral imaging, including halogen lamps, spectral sensors, and different types of asphalt pavement samples;

[0007] 2) Under halogen lamp illumination, replace different types of asphalt pavement samples and use a spectral sensor as a measuring device to obtain and save multiple irradiance spectra of different asphalt pavement samples and different wavelengths in the visible light spectrum;

[0008] 3) Data processing is performed on the irradiance spectrum obtained in step 2) to calculate the average irradiance of each wavelength for the water-logged, dry and black ice asphalt pavement samples and record them as In addition, the average irradiance of the white board under the same wavelength and lighting conditions is measured separately and recorded as

[0009] 4) Calculate the corresponding relative irradiance using the average irradiance of the wet, dry, and black ice asphalt pavement samples and the average irradiance of the whiteboard obtained in step 3);

[0010] 5) Using the same lighting conditions as in step 2) to illuminate the asphalt pavement to be tested, using a spectral sensor as a measuring device, obtain multiple irradiance spectra of the asphalt pavement to be tested at different wavelengths within the visible light spectrum range, and then process them according to the method in step 3) to calculate the average irradiance of the asphalt pavement to be tested at each wavelength And compared with the average irradiance of the white board Compare and get the relative irradiance R1 of the asphalt pavement to be tested;

[0011] 6) Using the relative irradiance of the flooded, dry, and black ice asphalt pavement samples obtained in step 4) and the relative irradiance R1 of the asphalt pavement to be tested obtained in step 5), calculate the Euclidean distance between the asphalt pavement to be tested and the flooded, dry, and black ice asphalt pavement samples under different wavelength conditions and record it as d. Finally, the condition of the asphalt pavement to be tested is determined based on the Euclidean distance.

[0012] In step 1), the halogen lamp and spectral sensor are respectively mounted on two spaced-apart support poles; asphalt pavement samples include three types: waterlogged, dry, and black ice. Each asphalt pavement sample is placed directly below the spectral sensor, and light from the halogen lamp is irradiated onto the asphalt pavement sample; the visible light spectrum collected by the spectral sensor ranges from 350 to 1070 nm, with a baud rate of 921,600 bps; and the rated power of the halogen lamp is 500 W.

[0013] In step 2), the distance between the spectral sensor and the asphalt pavement sample is 10 cm; and the spectral sensor saves the irradiance spectrum in a single frame manner.

[0014] In step 4), the relative irradiance of the flooded asphalt pavement sample is calculated as follows:

[0015]

[0016] The relative irradiance calculation formula of the dry asphalt pavement sample is as follows:

[0017]

[0018] The relative irradiance calculation formula of the black ice asphalt pavement sample is as follows:

[0019]

[0020] In step 5), the relative irradiance calculation formula of the asphalt pavement to be tested is as follows:

[0021]

[0022] In step 6), the Euclidean distance formula of the irradiance between the asphalt road surface to be measured and the flooded road surface is:

[0023]

[0024] The Euclidean distance formula between the irradiance of the asphalt pavement to be measured and the dry pavement is:

[0025]

[0026] The Euclidean distance formula of the irradiance of the asphalt road surface to be measured and the black ice road surface is:

[0027]

[0028] The method for judging the state of the asphalt road surface to be tested based on the above Euclidean distance is:

[0029] (1) When d v1 <d v2 <d v3 When , it is judged that the asphalt road surface to be tested is in a waterlogged state;

[0030] (2) When d v2 <d v1 <d v3 When , it is judged that the asphalt pavement to be tested is in a dry state;

[0031] (3) When d v3 <d v1 <d v2 When the asphalt road surface to be tested is judged to be in a black ice state.

[0032] The present invention has the following beneficial effects:

[0033] Non-contact multispectral analysis can be used to process irradiance data under different asphalt pavement conditions to achieve classified detection of different asphalt pavement conditions, significantly improving the accuracy and reliability of black ice detection. It can effectively prevent safety accidents caused by black ice on airport runways and has important engineering application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a schematic diagram of the installation location of the airport runway pavement black ice detection system based on multispectral imaging in the present invention. DETAILED DESCRIPTION

[0035] The method for detecting black ice on an airport runway pavement based on multispectral imaging provided by the present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0036] The method for detecting black ice on airport runway pavement based on multispectral imaging provided by the present invention comprises the following steps performed in sequence:

[0037] 1) Establish Figure 1 The airport runway pavement black ice detection system shown here, based on multispectral imaging, includes a halogen lamp, a spectral sensor, and different types of asphalt pavement samples;

[0038] The halogen lamp 1 and spectral sensor 2 are respectively mounted on two spaced-apart support poles. Asphalt pavement samples 3 include three types: waterlogged, dry, and black ice. Each asphalt pavement sample 3 is placed directly below the spectral sensor 2, and light emitted by the halogen lamp 1 is irradiated on the asphalt pavement sample 3. The visible light spectrum collected by the spectral sensor 2 has a range of 350 to 1070 nm and a baud rate of 921,600 bps. The rated power of the halogen lamp 1 is 500 W.

[0039] 2) Under halogen lamp illumination, replace different types of asphalt pavement samples and use a spectral sensor as a measuring device to obtain and save multiple irradiance spectra of different asphalt pavement samples and different wavelengths in the visible light spectrum;

[0040] The distance between the spectral sensor 2 and the asphalt pavement sample 3 is 10 cm; and the spectral sensor 2 saves the irradiance spectrum in a single frame manner.

[0041] 3) Data processing is performed on the irradiance spectrum obtained in step 2) to calculate the average irradiance of each wavelength for the water-logged, dry and black ice asphalt pavement samples and record them as In addition, the average irradiance of the white board under the same wavelength and lighting conditions is measured separately and recorded as

[0042] 4) Calculate the corresponding relative irradiance using the average irradiance of the wet, dry, and black ice asphalt pavement samples and the average irradiance of the whiteboard obtained in step 3);

[0043] The relative irradiance calculation formula of the flooded asphalt pavement sample 3 is as follows:

[0044]

[0045] The relative irradiance calculation formula of the dry asphalt pavement sample 3 is as follows:

[0046]

[0047] The relative irradiance calculation formula of the black ice asphalt pavement sample 3 is as follows:

[0048]

[0049] 5) Using the same lighting conditions as in step 2) to illuminate the asphalt pavement to be tested, using a spectral sensor as a measuring device, obtain multiple irradiance spectra of the asphalt pavement to be tested at different wavelengths within the visible light spectrum range, and then process them according to the method in step 3) to calculate the average irradiance of the asphalt pavement to be tested at each wavelength And compared with the average irradiance of the white board Compare and get the relative irradiance R1 of the asphalt pavement to be tested;

[0050] The calculation formula for the relative irradiance of the asphalt pavement to be tested is as follows:

[0051]

[0052] 6) Using the relative irradiances of the flooded, dry, and black ice asphalt pavement samples obtained in step 4) and the relative irradiance R1 of the asphalt pavement to be tested obtained in step 5), calculate the Euclidean distances between the asphalt pavement to be tested and the flooded, dry, and black ice asphalt pavement samples under different wavelength conditions, and record them as d. Finally, determine the condition of the asphalt pavement to be tested based on the Euclidean distances.

[0053] The Euclidean distance formula of the irradiance between the asphalt pavement to be tested and the flooded pavement is:

[0054]

[0055] The Euclidean distance formula between the irradiance of the asphalt pavement to be measured and the dry pavement is:

[0056]

[0057] The Euclidean distance formula of the irradiance of the asphalt road surface to be measured and the black ice road surface is:

[0058]

[0059] The method for judging the state of the asphalt road surface to be tested based on the above Euclidean distance is:

[0060] (1) When d v1 <d v2 <d v3 When , it is judged that the asphalt road surface to be tested is in a waterlogged state;

[0061] (2) When d v2 <d v1 <d v3 When d v3 <d v1 <d v2 When the asphalt road surface to be tested is judged to be in a black ice state.

Claims

1. A method for detecting black ice on airport runway pavement based on multispectral imaging, characterized by: The method for detecting black ice on airport runway pavement based on multispectral imaging comprises the following steps performed in sequence: 1) Establish an airport runway pavement black ice detection system based on multispectral imaging, including halogen lamps, spectral sensors, and different types of asphalt pavement samples; 2) Under halogen lamp illumination, replace different types of asphalt pavement samples and use a spectral sensor as a measuring device to obtain and save multiple irradiance spectra of different asphalt pavement samples and different wavelengths in the visible light spectrum; 3) Data processing is performed on the irradiance spectrum obtained in step 2), and the average irradiance of the water-logged, dry and black ice asphalt pavement samples at each wavelength is calculated and recorded as In addition, the average irradiance of the white board under the same wavelength and lighting conditions is measured separately and recorded as 4) Calculate the corresponding relative irradiance using the average irradiance of the wet, dry, and black ice asphalt pavement samples and the average irradiance of the whiteboard obtained in step 3); 5) Using the same lighting conditions as in step 2) to illuminate the asphalt pavement to be tested, using a spectral sensor as a measuring device, obtain multiple irradiance spectra of the asphalt pavement to be tested at different wavelengths within the visible light spectrum range, and then process them according to the method in step 3) to calculate the average irradiance of the asphalt pavement to be tested at each wavelength And compared with the average irradiance of the white board Compare and get the relative irradiance R1 of the asphalt pavement to be tested; 6) Using the relative irradiance of the flooded, dry, and black ice asphalt pavement samples obtained in step 4) and the relative irradiance R1 of the asphalt pavement to be tested obtained in step 5), calculate the Euclidean distance between the asphalt pavement to be tested and the flooded, dry, and black ice asphalt pavement samples under different wavelength conditions and record it as d. Finally, the condition of the asphalt pavement to be tested is determined based on the Euclidean distance.

2. The method for detecting black ice on airport runway pavement based on multispectral imaging according to claim 1, characterized in that: In step 1), the halogen lamp (1) and the spectrum sensor (2) are respectively installed on two support rods set at a distance; the asphalt pavement samples (3) include three types: water accumulation, dryness and black ice, each asphalt pavement sample (3) is placed directly below the spectrum sensor (2), and the light emitted by the halogen lamp (1) is irradiated on the asphalt pavement sample (3); the visible light spectrum collected by the spectrum sensor (2) has a range of 350 to 1070 nm and a baud rate of 921600 bps; the rated power of the halogen lamp (1) is 500 W.

3. The method for detecting black ice on airport runway pavement based on multispectral imaging according to claim 1, characterized in that: In step 2), the distance between the spectrum sensor (2) and the asphalt pavement sample (3) is 10 cm; and the spectrum sensor (2) saves the irradiance spectrum in a single-frame manner.

4. The method for detecting black ice on airport runway pavement based on multispectral imaging according to claim 1, characterized in that: In step 4), the relative irradiance of the waterlogged asphalt pavement sample (3) is calculated using the following formula: The relative irradiance calculation formula of the dry asphalt pavement sample (3) is as follows: The relative irradiance calculation formula of the black ice asphalt pavement sample (3) is as follows:

5. The method for detecting black ice on airport runway pavement based on multispectral imaging according to claim 1, characterized in that: In step 5), the relative irradiance calculation formula of the asphalt pavement to be tested is as follows:

6. The method for detecting black ice on airport runway pavement based on multispectral imaging according to claim 1, characterized in that: In step 6), the Euclidean distance formula of the irradiance between the asphalt road surface to be measured and the flooded road surface is: The Euclidean distance formula between the irradiance of the asphalt pavement to be measured and the dry pavement is: The Euclidean distance formula of the irradiance of the asphalt road surface to be measured and the black ice road surface is: The method for judging the state of the asphalt road surface to be tested based on the above Euclidean distance is: (1) When d v1 <d v2 <d v3 When , it is judged that the asphalt road surface to be tested is in a waterlogged state; (2) When d v2 <d v1 <d v3 When , it is judged that the asphalt pavement to be tested is in a dry state; (3) When d v3 <d v1 <d v2 When the asphalt road surface to be tested is judged to be in a black ice state.

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