2020 Vol. 44, No. 4
In order to meet the measurement speed requirement when measuring the equivalent thermal focal length of laser material thermal effect based on the Talbot interferometer, a fast algorithm for solving the Moiré fringe angle was proposed. The influence factors of measuring speed by traditional frequency iterative method were analyzed. Based on the similarity of the iterative computing coordinate value and the separability of discrete Fourier transform, the common points of the coordinate points containing decimal are separated from coordinate operation of the spectrum value solution process. The common is filtered by the Fourier transform exponential term, and the different parts are combined operation on the basis of extracting similarity. The 2-D image is reduced to 1-D, and the index items of different parts are limited to the minimal knowable range, which greatly facilitates the use of table-referring and bit-wise operation. The experimental results show that the measurement time with the same configuration computer is reduced from 15s to 0.4s on the premise of ensuring the measurement accuracy, and the measurement speed is increased by 38 times. The application requirement of the equivalent thermal focal length measurement was well satisfied.
Adaptive optics technology was widely used in large-scale ground-based optical telescope to correct the wavefront distortion caused by atmospheric disturbance, make the telescope reach the resolution near diffraction limit, and realize the clear imag-ing of the observed object. As the beacon source of adaptive optical correction, laser sodium guide star was one of the core technologies of adaptive optical telescope. The latest research progress of the new sodium beacon laser was demonstrated, include the 589nm optical pumped vertical external cavity surface emitting semiconductor sodium guide star laser and the all solid-state laser with Dy3+-doped crystal as gain medium, which can directly emit 589nm laser. Due to their advantages of small size, high efficiency, high reliability, low cost and easy maintenance, these schemes are considered as the possible development direction of the new generation of sodium guide star lasers.
In order to study the laser damage threshold of an uncooled microbolometer, according to the construction and imaging principle of uncooled microbolometer, the temperature response mechanism of the pixel was analyzed, and the formula for calculating the temperature increment of the laser under the zero offset and single offset time was derived. A finite element analysis model of laser irradiated uncooled microbolometer was established. Simulation was carried out by loading the heat source load in combination with actual working conditions. Then the process of soft damage caused by laser was simulated. The conclusion was drawn: laser soft damage threshold approximate calculation of the pixel temperature response under zero bias conditions can be used to meet 3% accuracy. This study provides a reference for the calculation of damage threshold for laser suppression interference infrared imaging systems.
In order to study the interference mechanism of near-infrared laser to image sensor, a monochromatic charge-coupled device(CCD) detector was irradiated by continuous laser with a wavelength of 1064nm. The interference phenomenon of laser to monochromatic camera was observed and the digital image collected by the experiment was processed. And the interference degree curves of monochromatic camera under different laser powers were extracted. After analysis, the following conclusions were obtained: CCD interference includes interference spot and crosstalk line. The higher the laser power is, the larger the interference spot radius is, and the crosstalk line is slowly widened. The more number of saturated pixels in the corresponding interference region, the more serious the interference degree. For the interference of 1064nm laser to monochromatic camera, the number of saturated pixels is almost linearly proportional to the laser power. Analysis of the new phenomena of regular dot-matrix and side-by-side crosstalk appearing in experimental phenomena is related to Fourier spectral properties of optical lenses. The fitting curve of the general interference process is derived by using the relevant formula. Finally, the interference process is simulated according to the characteristics of the CCD basic pixel structure capacitor potential trap and the carrier overflow mode. The simulation results are basically consistent with the experimental data.
In order to study the properties of the Goos-Hnchen shift in semi-infinite hexagonal boron nitride covered by graphene, the influence of structural parameters on the Goos-Hnchen shift was analysised by using the transfer matrix method. The results show that: By reasonably adjusting the chemical potential or layer number of graphene, the transformation of Goos-Hnchen shift from positive to negative can be realized. By selecting the appropriate parameters, large Goos-Hnchen shifts can be realized and the maximum value is about 450 times of the wavelength. It is of great significance for the design of optical switches, optical couplers and other applications.
In order to solve the input saturation problem in the optoelectronic servo platform, a sliding mode control algorithm based on the transition process is adopted. The transition process algorithm is designed based on the time-optimal theory, which makes the hopping input signal become a slowly rising signal, so that the initial tracking error of the system is decrease, thus avoiding the input saturation phenomenon and greatly improving the system stability. After theoretical analysis and experimental verification, the results show that the proposed method can effectively eliminate the input saturation phenomenon and is suitable for target tracking of the optoelectronic servo platform and has important research and application value.
In order to propagate reactionary thinking and disrupt social security management, reactionary forces often write and post various reactionary slogans with a marker. Undoubtedly, it's significant to identify the marker ink in forensic science. The paper collected and analyzed the infrared fingerprint data of 40 black marker pens from 5 brands including Guangbo and so on. Pre-processing used multi-scatter correction, peak area normalization, automatic baseline correction, and Savitzky-Golay smoothing to create a black marker ink identification model based on multilayer perceptron (MLP). The result showed that the infrared fingerprint can reflect the subtle changes of the molecular structure, which can effectively distinguish the water-based and oil-based markers. For 4 oily marker samples, it was found that the MLP model has the best feature extraction on the 30-dimensional matrix, whose accuracy rate reached 100%. Besides, feature 12, feature 26, and feature 17 were of the highest importance in model construction, with 0.0355, 0.0347, and 0.0346, respectively. Among them, the Letu brand samples had a high degree of convergence, concentrated distribution, and the difference in ink composition and content were small, while the Baoke brand samples were the opposite. In the confirmatory analysis, 8 samples to be determined achieved 100% accuracy, which was ideal. In summary, infrared fingerprints combined with multilayer perceptron can achieve accurate identification between black marker ink brands. The method improved the efficiency of inspection and identification, reduced the cost of identification and fulfilled the rapid and accurate inspection goal for frontline law enforcement personnel, which has certain universality and reference significance.
Point cloud data of mountain power corridor space can be used to assist in path planning, reduce the probability of the drone flight accidents and effectively improve the efficiency and accuracy of the inspection with drones. In the process of path planning, the effectiveness of flight measurement and flight efficiency need to be taken into account. However, there is no effective way to solve this problem. In order to improve the effectiveness of flight measurement and flight efficiency, a path planning method combining sensor measurement characteristics was proposed, which was based on the maximum distance and angle of laser measurement, with flight efficiency and inspection target position as the constraints. The trajectory of flight was obtained by solving the planning equation, so as to ensure the safety and efficiency of the drone mountain environmental inspection. The experimental results show that the planning optimization effect is 7.58%, 11.18% and 13.33%, respectively, with consideration of the maximum measured distance d and measuring angle θ evaluated by the combined laser sensor of Velodyne VLP-16, RS-LiDAR-16 and HDL-32E. Therefore, the validity and correctness of the path planning method of laser scanning in mountain areas were verified.
In order to improve the current situation that thin-walled part such as harvester cutter are prone to deformation during laser cladding for their performance enhancement, three different Fe-based alloy cladding coatings were prepared by Nd:YAG laser processing system under the scanning paths of Hilbert fractal, contour offset, and grating. The data of the deformation of the substrate and the bath depth were then obtained. The results show that the bath depth at the center of the contour offset scanning path is the largest, which is 0.75mm, and the deformation of the sample reaches 0.30mm; there is a positive correlation between the thermal gradient of the bath and its vicinity and the deformation of the substrate in the laser cladding process. The higher the temperature is, the faster the change is, the greater the thermal stress is, and the greater the tendency of deformation is. The bath depth in grating scanning path increases with time and the thermal gradient is small, so the deformation tendency of the substrate is weak, and the macroscopic feature is the best, which is suitable for the scanning path of laser cladding of thin-walled part. This study has guiding significance for laser cladding on thin-walled part.
In order to make full use of the characteristics of the passiveness, real-time nature of the information in the visual image, and the self-creation of the on-board controller, to effectively solve the problems of easy interference, delay, and constraints of the drone signal source, the "十" dynamic structure and control principle of the quad-rotor unmarned aerial vehide(UAV) and the relationship between the posture equation and the dynamic equation during the flight of the UAV were analyzed. The conversion between the six-degree-of-freedom information of the quad-rotor UAV and the four elements of flight control information were completed. An autonomous control algorithm for unmanned aerial vehicle vision images based on cooperative target matching was then designed. The computer simulation verification proves that the algorithm can realize the autonomous landing of a four-rotor drone in a simple environment. This research will help the autonomous and intelligent development of drones.
In order to solve the influence of noise spot on extraction accuracy in the online structured light three-dimensional measurement, the center line of laser stripe was extracted by density clustering gray centroid extraction algorithm. The method consists of two stages: The pre-extraction of center line and the final extraction of center line. The pre-extraction stage realizes the simultaneous extraction of the center line of laser and spot. In the final extraction stage, the connectivity-based density clustering algorithm is used to preserve the laser centerline and eliminate the noise spot. In the simulation experiment stage, the image with the size of 600pixel×600pixel and the laser center line was denoised. The root mean square error and the running time of each point between the extracted result and the real center line were used as the inspection criteria. The results show that the root mean square error of high brightness anisotropic spot, high brightness small area spot, and high brightness point noise image was respectively reduced by 12.59pixel, 15.12pixel, and 83.36pixel, and the time complexity was respectively increased by 0.383s, 0.412s, and 0.416s. Compared with the traditional gray centroid method, this method has higher extraction accuracy, approximate time complexity, and better robustness to noise spot.
In order to meet the need of chaotic secure communication, a scheme of generating high quality chaotic optical signals by mutually coupled semiconductor ring lasers was proposed. The time series, power spectrum and autocorrelation coefficient distributions under various parameters were obtained by numerical simulation, and the theoretical analysis was carried out. The results show that under certain parameters, the laser can exhibit single-period, multi-period and chaotic dynamic states. In the case of large frequency detuning, the delay characteristics of chaos are well suppressed. By scanning injection parameters in a wide range, the chaotic signal with a maximum bandwidth of 14.0GHz and a low time delay signature can be obtained, which can significantly improve the transmission rate and security of chaotic secure communication. The results of this paper can provide some theoretical reference for the application of ring laser in chaotic secure communication.
To identify aircraft wake vortex by pulsed doppler LiDAR's characteristics, a classification model based on k-nearest neighbor (KNN) was established in this paper. This approach by combining Hallock-Burnham model with pulsed doppler LiDAR's characteristics to extract the feature parameters of radial velocity of wind field was pursued. Based on the test dataset, the KNN was employed to identify aircraft wake vortex in the context of nonuniform wind field. The performance of the proposed method was evaluated in terms of the accuracy (ACC) and the area under ROC curve (AUC). The ACC and the AUC of our technique on test dataset are 0.772 and 0.855, respectively. Experimental results are presented to illustrate the validity and robustness of the proposed approach to aircraft wake vortex.
In order to detect the content of benzoic acid in corn flour, control the amount of benzoic acid used in corn flour to improve food safety grade, the content of benzoic acid in corn flour was studied using terahertz spectroscopy technology, and the terahertz benzoic acid spectral data of different mass fractions in corn flour was obtained. In order to improve the accuracy of the model, pre-processing methods such as moving average smoothing algorithm, standard normal transformation, multi-scattering correction, baseline correction, and normalization were used to eliminate the original spectral noise and useless information. The least squares support vector machine(LS-SVM), partial least squares(PLS), and multiple linear regression(MLR) spectroscopy models were constructed, and the model samples were not used for model evaluation. The model was evaluated based on the prediction set correlation coefficient eRMSEP and the prediction set root mean square error Rp. The results show that the least squares support vector machine model with the original terahertz time-domain spectral preprocessing has the strongest evaluation ability. The correlation coefficient of the prediction set Rp=0.9958, and the root mean square error of the prediction(RMSEP) set eRMSEP=0.0057, indicating the metrology method of THz-TDS binding chemistry can be used to detect the quantitative determination of benzoic acid in corn flour.
In order to extract the features of spatial information and spectral information in hyperspectral image, a 3-D convolutional recursive neural network (3-D-CRNN) hyperspectral image classification method was proposed. Firstly, 3-D convolutional neural network was used to extract local spatial feature information of target pixel, then bidirectional circular neural network was used to train spectral data fused with local spatial information, and joint features of spatial spectrum were extracted. Finally, Softmax loss function was used to train classifier to realize classification. The 3-D-CRNN model did not require complex pre-processing and post-processing of hyperspectral image, which can realize end-to-end training and fully extract semantic information in spatial and spectral data. Experimental results show that compared with other deep learning-based classification methods, the overall classification accuracy of the method in this paper is 99.94% and 98.81% respectively in Pavia University and Indian Pines data set, effectively improving the classification accuracy and efficiency of hyperspectral image. This method has some enlightening significance for feature extraction of hyperspectral image.
In order to study the effect of the active agent on the temperature of the molten pool of laser welding samples, the ANSYS 3-D finite element model of active laser welding was established with 304 stainless steel thick plate as the object. In the model, the welding temperature field was numerically simulated, and the infrared thermal imager was used to monitor the melting. Based on the comprehensive numerical calculation and experimental test data, the temperature variation trend of the specimens coated with different active agents and uncoated active agents during laser welding was compared and analyzed. The results show that the numerical simulation results are basically consistent with the experimental results. The application of the active agent does not have a significant effect on the temperature field distribution, but the peak temperature of the molten pool is slightly changed. Compared with the uncoated active agent welded specimens, SiO2 and TiO2 active agent respectively raises the peak temperature of the molten pool by about 7% to 9%, and the NaF active agent reduces the peak temperature of the molten pool by about 5%. This research will enrich and develop the basic theory of active laser welding thick plates, and provide important theoretical and experimental basis for the popularization and application of active laser welding.
In order to eliminate the noise points in the process of collecting laser point cloud and avoid the impact of noise the data quality of the point cloud, especially some isolated outliers. The scattered and noisy point cloud is transformed into regular and high-precision point cloud, and the method of point cloud denoising based on principal component analysis and surface fitting is adopted. In this paper, a point cloud denoising method based on principal component analysis and surface fitting was proposed. Firstly, the principal component analysis method of point cloud region was proposed. Then, the principal component analysis normal vector was used for rough denoising, and the rough denoising point cloud was used for surface fitting. Finally, the point cloud was filtered according to the synthetic distance between the point and the surface. The experimental result shows that the denoising effect is accurate. From the above experimental results and analysis, it can be seen that this method has high filtering accuracy through fitting operation. The algorithm is simple in structure and can retain the details effectively, the error of the best filter performance is only 0.018mm. This study provides a reference for the denoising and filtering of scattered laser point clouds.
The visibility errors induced by the multiple-scattering effects are further discussed considering the system parameters of the laser transmissometers, which have been regarded as promising visibility meters used in airports around the world. Based on the size distributions of the advection fog and radiation fog, the transmission of photons is simulated numerically using the Monte-Carlo method. It is noted that the multiple-scattering effects would become more serious for larger water content of the fog, which may cause significant visibility errors as the outputs of the transmissometers. The relative error of transmittance of radiation fog is even possible to achieve 116.76%, and the error of visibility caused by multiple scattering of radiation fog is 19.30% when the diameter of receiver is 100cm. The simulation results further reveal that reducing the receiver aperture may sufficiently suppress the multiple-scattering effects. It is necessary to consider the multiple-scattering effects on the visibility measurement especially for the low-visibility atmosphere, e.g., in dense fog and haze, which gives us important hints on the visibility measurement of laser transmissometers in dense fog and haze.
In order to solve the problem of low accuracy and robustness of power line extraction in complex environment, an automatic power line extraction method based on laser point cloud was proposed. The main direction of transmission line was determined by principal component analysis, and the long distance transmission corridor was divided into several spatial grids to deal with the disturbance of vegetation point clouds on the extraction algorithm when the terrain changes. Then a new top-down filtering algorithm was used to eliminate the object points in each spatial grid, and the automatic separation of power lines and towers was realized according to the difference of point cloud density distribution. In addition, a radius search algorithm is proposed to process the separated results and obtain the laser point cloud data of a single power line. The results show that the proposed method has a high accuracy of 99.69%. It has good robustness for different connection tower types and different terrain. This research has good engineering application value in the field of automatic analysis of transmission channel spatial structure and intelligent patrol inspection.
The method of extracting features of model, which was the core of tracking, was employed to evaluate the fidelity of infrared simulation model. By analyzing the kernel of tracking process, the image of a partial field around the center of target was chosen to evaluate the target model. Based on the existing evaluating methods of the infrared simulation model, a typical object-tracking algorithm was adopted to design the experiment. Following theoretical analysis, the corresponding experiment was then carried out. Result shows that the similar target model is more than 2 times as much as the dissimilar model based on the key features extracting method, and the difference between them can even get to 10 times. Therefore, the key feature extraction algorithm is a practical and feasible method to verify the validity of the target model. This evaluation method can provide theoretical guidance for the evaluation of model fidelity in the field of infrared target detection.
In order to solve the problem that the traditional modeling detection algorithm for spotted small target is susceptible to the dim and spotted targets, resulting in the loss of small target or the false detection that treat the background information as the target during the detection process, a more effective multi-scale spotted small target modeling algorithm was adopted. By modeling the background and suspicious target, the suspicious target image could be obtained. Finally, a threshold segmentation algorithm was used to extract the real target from the suspicious target, and then the theoretical analysis and experimental verification were carried out. The results show that under the same data set, the trajectory of small target dected by this algorithm is closer to the real trajectory than those by other algorithms. This research is helpful to improve the accuracy of small targets detection.