Foreign object debris (FOD) on airport runways is an important factor affecting aircraft flight safety, and current FOD detection technologies all have obvious deficiencies. In this paper, an indoor near-infrared (NIR) hyperspectral image data acquisition system with a wavelength range of 900-1700nm was built. The 14 samples of 6 common FODs and airport concrete runways were divided into reference and test sample sets, and the atlas data were collected for two common application scenarios. Preprocessing was performed on the reference sample set of hyperspectral images and reference spectral curves were extracted for 7 types of samples. Six spectral matching algorithms based on spectral angle matching (SAM), spectral information divergence (SID), spectral correlation coefficient (SCC) and their combinations are used to classify pixels one by one. By comparing the classification map, overall accuracy (OA), average accuracy (AA), and Kappa coefficient, a NIR hyperspectral FOD detection method based on SAM-SID (threshold Sc=40 pixel) criterion is obtained. The proposed method obtained ideal classification maps for the test sample set, with OA, AA and Kappa coefficients reaching 92%, 82% and 0.82, respectively, thus achieving good validation.
Damage to the skin coating of the Cessna 172R aircraft is an unavoidable and significant issue due to long flight training. Traditional detection methods are easy to missed and false detections, and hyperspectral technology can significantly improve. The spectral curves of the damaged and undamaged skin coating pixels in the near-infrared band (900-1700 nm) of the Cessna 172R aircraft skin samples were used to establish three spectral indices: ASCI-I, ASCI-II, and ASCI-III. Then the decision tree is used to perform recognition experiments on the two types of skin samples. The experimental results show that the decision tree model based on ASCI-I has the best recognition performance. Its global image recognition results are closely related to the spatial distribution of the actual targets. The Producer accuracy, User accuracy, and overall classification accuracy are all over 90%, and the Kappa coefficient is greater than 0.88.
At present, there are few studies on nondestructive testing of aircraft surface based on hyperspectral imaging at home and abroad. Therefore, an indoor near infrared (NIR) hyperspectral damage detection system with a spectral resolution of 5nm was established, and the paint damage on the sample surface was identified. The reflectance calibration, average reflectance calculation and principal component analysis (PCA) dimensionality reduction were performed on the collected hyperspectral data. On this basis, the unsupervised classification iterative self-organizing Data analysis algorithm (ISODATA) is used to identify the damaged samples. The results show that the spectral curves of the damaged and undamaged pixels of the sample are significantly different at about 910nm. The first 10 principal components selected can contain 97% of the sample data information, which can realize the effective identification of damage samples based on ISODATA. In this study, paint damage was taken as an experimental sample to verify the feasibility of using near-infrared hyperspectral imaging technology for damage identification. In addition, preliminary outfield experiment results also show that it is feasible to apply this technology to aircraft surface damage detection.
Monitoring the formation process and occurrence state of methane in abyssal gas-liquid-hydrate coexistent system is the premise for gas hydrate research and exploitation, and the key lies in real time, synchronous and in-situ acquisition of multi state parameters, like concentration, temperature, pressure of methane. In this paper, we propose a novel multi parameter in situ methane sensor (Submarine Methane Imaging Interference Spectrometer, SMIIS) that can simultaneously measure concentration, temperature and pressure information of submarine methane. Then to evaluate SMIIS’s feasibility and performance, we build SMIIS’s simulation model and analyze its forward interferogram. The signal-to-noise ratios (SNRs) of the simulation interference fringes for the six spectral lines of methane are in the range of (3 - 618). The detection sensitivities for concentration, temperature and pressure measurements can reach to 0.5 nmol/L, 0.5 K, and 0.05 MPa, respectively. The results indicate that the preliminary design of SMIIS is feasible. After further testing and improvement, this system will have the potential to be applied to the seabed methane detection.
The propagation characteristics, including beam propagation factor (i.e., M2-factor) and characteristic distances, of truncated Airy (TA) beams is studied in atmospheric turbulence. Based on the extended Huygens-Fresnel principle and the second moments of the Wigner distribution function (WDF), the analytical expressions of the M2-factor of the TA beam in a turbulent atmosphere are derived. By using Andrews spectrum as the atmospheric turbulence model, numerical examples of M2-factor, relative M2-factor, turbulent Rayleigh distance and turbulence distance are given. The results show that the M2-factor, which depends on the truncation factor and the initial first lobe width, decreases with the decrease of the structure constant of turbulence, and with the increase of the inner scale of turbulence. The relative M2-factor decreases with decreasing structure constant of turbulence and truncation factor and with increasing the inner scale. There exists an optimum initial first lobe width which corresponds the minimum of the M2-factor. The turbulent Rayleigh range increases with decreasing truncation factor and inner scale. The turbulence distance increases with decreasing truncation factor and increasing inner scale.
The beam wander properties of electromagnetic Gaussian Schell-model (EGSM) beam propagating in atmospheric turbulence are investigated based on the extended Huygens–Fresnel principle, the second-order moments of the Wigner distribution function (WDF) and the Andrews beam wander theory. The simplified integral formulae for the root-mean-square (rms) beam wander and the relative beam wander of EGSM beams in turbulence have been derived. Our results indicate that in a strong turbulence, the rms beam wander increases obviously with increasing inner scale, and the influence of inner scale of turbulence on the rms beam wander can not be ignored in strong turbulence. The evolution behaviors of the rms beam wander and relative beam wander in atmospheric turbulence are quite different which depend on the initial beam width, the transverse coherence width, the inner and outer scales of turbulence. Both the rms beam wander and relative beam wander can be effectively reduced by increasing the initial beam width and decreasing the transverse coherence width.
For the two-point spherical wave structure function, we propose a modified quadratic approximation, which can be used to investigate the second-order coherence properties (such as the beam spreading, average intensity, cross-spectral density function) of partially coherent beams through the turbulent atmosphere. We prove that the modified quadratic approximation, different from usual one, can be used to study the effects of inner and outer scales of turbulence, and is better than the usual one for a less coherent beam or for a very strong turbulence. A more accurately analytical expression for average intensity of Gaussian-Schell model beams is derived based on the modified quadratic approximation. These results are also illustrated by investigating the average intensity for Gaussian-Schell model beams in turbulence.
The continuous wavelet transform (CWT) introduces an expandable spatial and frequency window which can overcome the inferiority of localization characteristic in Fourier transform and windowed Fourier transform. The CWT method is widely applied in the non-stationary signal analysis field including optical 3D shape reconstruction with remarkable performance. In optical 3D surface measurement, the performance of CWT for optical fringe pattern phase reconstruction usually depends on the choice of wavelet function. A large kind of wavelet functions of CWT, such as Mexican Hat wavelet, Morlet wavelet, DOG wavelet, Gabor wavelet and so on, can be generated from Gauss wavelet function. However, so far, application of the Gauss wavelet transform (GWT) method (i.e. CWT with Gauss wavelet function) in optical profilometry is few reported. In this paper, the method using GWT for optical fringe pattern phase reconstruction is presented first and the comparisons between real and complex GWT methods are discussed in detail. The examples of numerical simulations are also given and analyzed. The results show that both the real GWT method along with a Hilbert transform and the complex GWT method can realize three-dimensional surface reconstruction; and the performance of reconstruction generally depends on the frequency domain appearance of Gauss wavelet functions. For the case of optical fringe pattern of large phase variation with position, the performance of real GWT is better than that of complex one due to complex Gauss series wavelets existing frequency sidelobes. Finally, the experiments are carried out and the experimental results agree well with our theoretical analysis.
Comparison and analysis for several usual types of atmospheric turbulence simulator are first given in this paper. Considering the Tatarskii spectrum and the conditions of laboratory, secondly, the numerical calculations of the M2 factor and the spatial and angular widths of coherent Gaussian beams in turbulence are performed. Finally, a kind of a hot-wind atmospheric turbulence generator is designed and its characteristics are analyzed. The results show that the turbulence generator is very suitable to use in studying the effects of turbulence on the M2 factor of cw laser beams. Also, the values of both the structure constant of refractive index fluctuations Cn2 and the inner scale of turbulence required by the generator are still in accordance with those of actual atmospheric turbulence.
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