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Issue 7 ， 2023
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Differential confocal radius of curvature measurement method for five-dimensional position monitoring
Abstract：To improve the measurement accuracy of the radius of curvature， a high-precision measurement method of a differential confocal radius of curvature based on a five-dimensional （5D） pose monitoring adjustment was proposed. On the basis of the differential confocal curvature radius measurement system， this method introduces a 5D position monitoring and adjustment structure by driving the measured part rotation on the detector to monitor the confocal trajectory. In addition， it enables measurement of the eccentric error of the spherical center point of the measured part and the measured optical axis， combined with two-dimensional （2D） translation and 2D angle adjustment to automatically compensate for the eccentric error. Further， it aims to ensure that the measured sample spherical center and the measured optical axis are in good agreement during the measurement process， eliminate the measurement cosine error caused by the deviation of the spherical center of the measured sample， and eliminate the influence of the sample posture error on the measurement accuracy of each installation. Based on the results obtained， repeatability measurements are significantly improved with the proposed method. Theoretical simulation and preliminary experimental results show that the repeatability of the proposed method for measuring the radius of curvature can reach 3.2×10-6. This method is shown to be an effective way of obtaining a precise measurement of the radius of curvature. At the same time， this method can also be extended to the measurement of the lens center deviation， focal length， thickness， lens group interval， and other parameters to improve the measurement repeatability of lens parameters.Keywords：Radius of curvature;laser differential confocal;five-dimensional position monitoring;five-dimensional position adjustment;cosine error- 382
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Published：2023-04-14 -
Effect of signal sampling on laser noise based on 3×3 interferometer and phase signal demodulation
Abstract：A laser linewidth measurement system based on an unbalanced Michelson interferometer achieved using a 3 × 3 coupler and phase signal demodulation is reported in this study. The signal processing section is based on phase signal demodulation technology， which can process the signal in real time and at high speed. Therefore， the frequency noise and linewidth of the laser under test could be obtained quickly. The system features a simple optical path structure， no active control， and stable repeatability of measurement results. However， it is necessary to consider whether the sampled signal contains the maximum and minimum values of the source signal simultaneously when using this scheme. Therefore， the effect on the frequency noise power spectral density of the laser under test is thoroughly discussed with respect to different sampling windows of 0.5， 0.4， 0.1， 0.05， and 0.01 s. Both simulation and experiment show that the amplitude of the laser frequency noise power spectral density calculated by the signal is too high， and that sampling signals with sampling windows of 0.1， 0.05， and 0.01 s do not contain the maximum and minimum of the source signal. A commercial laser with a wavelength of 1.5 μm and a self-made laser in our laboratory with a wavelength of 2 μm are measured using β-separation line method. The results show that the linewidth of the commercial laser in the 1.5 μm band is 5 kHz， with a measurement time of 2 ms. It also shows that this conclusion can be extended to the entire band.Keywords：single-frequency narrow linewidth laser;line width measurement;frequency noise;phase signal demodulation- 188
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Published：2023-04-14 -
Spectropolarimetric measurement system based on spatially modulated heterodyne interference
Abstract：The design goals of a spectropolarimetric system are higher spectropolarimetric resolution， a smaller and lighter system， and static measurement of the full Stokes spectrum. Therefore， the spatially modulated heterodyne interference spectropolarimetric system， which combines the technologies of intensity modulation and spatial heterodyne was proposed. While the process of all mathematical derivation was displayed， the principle and structure of the system were presented and a theoretical analysis of the interferogram data acquisition and full Stokes parameters demodulation restoration was carried out. The matching modulator module was designed and a complete design example was finished based on the parameters of the spatial heterodyne spectrometer used. A principle experimental device of spatially modulated heterodyne interference spectropolarimetric system was established in the laboratory， and the feasibility of the principle and measurement data processing flow of the system was verified by analyzing the measurement experiments and experimental data of linearly polarized light with a known polarization state. The measurement and analysis results of the experimental data are consistent with the theoretical results， and the error is less than 3% This verifies the feasibility of principle of the spatial modulation heterodyne interference spectropolarimetric system.Keywords：spectropolarimetric measurement;intensity modulation;demodulation;spatial heterodyne spectroscopy- 136
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Published：2023-04-14 -
Laser triangular spot positioning combined with cross-correlation and B-spline interpolation
Abstract：Laser triangulation spot location is usually affected by the skewness of the image spot. To improve the measurement accuracy and surface adaptability of the laser triangulation displacement sensor by analyzing the skewness characteristics of the laser triangulation spot， this paper proposes a novel spot location algorithm based on cross-correlation and non-uniform rational B-spline interpolation. First， a filtering method combining time and space domain is adopted for the spot signal to reduce external noise interference. Subsequently， the calibration spot is matched to perform the cross-correlation operation， and the pixel-level correlation coefficient distribution is determined by maximizing the grayscale and position similarity constraints of light intensity distribution. Finally， the correlation coefficient sequence is subdivided by cubic non-uniform rational B-spline interpolation to achieve sub-pixel centroid location. Furthermore， the algorithm is verified in the laser triangulation displacement sensor， and the obtained results indicate that the measurement repeatability error is reduced to 0.4 μm by combining cross correlation and non-uniform rational B-spline interpolation subdivision. Compared with the conventional positioning algorithm， the accuracy is significantly improved； the neighborhood calibration spot template adopted in the cross-correlation algorithm is not only easy to obtain， with higher geometric similarity， but also more adaptive to different object surface characteristics. In general， this method exhibits high precision and strong adaptability， which provides a novel technical approach to effectively improving the performance of laser triangular displacement sensors.Keywords：laser triangulation;spot center;positioning error;cross-correlation;non-uniform rational B-spline- 196
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Published：2023-04-14 -
Calibration of signal-to-noise ratio of sub focal plane polarization image sensors
Abstract：To calibration the signal-to-noise ratio（SNR）of split-focus plane polarization image sensors， a calibration experiment of the SNR of each channel of a split-focus plane polarization image sensor was designed. The SNR parameters of the split-focus plane polarization image sensor were studied in terms of their influence on the polarization angle measurement results， the SNR calibration principle， and the calibration experiment procedure. The calibration principle of SNR was obtained based on the structure of the split-focus plane polarization sensor and the mathematical model of the digital image sensor. Then， the polarization angle measurement results were simulated under different SNR and different incident angle line polarization light cases. Subsequently， the device structure and experimental procedure of the calibration experiment were designed according to the calibration principle. Finally， an actual calibration was performed and the experimental data were analyzed. The simulation results show that the larger the SNR of the focal plane polarization image sensor， the higher the accuracy of polarization angle measurement， and the angle of incident polarized light also affects the measurement accuracy. The actual test results of the SNR of each channel of the focal plane polarization image sensor show that the difference between the calibration value and the index value is no more than 0.55 dB.The experimental results prove that the method is accurate and effective， and can better accomplish the calibration task of SNR for each channel of the split-focus plane polarization image sensor.Keywords：measurement technology and instruments;polarization image sensor;focal plane;signal-to-noise ratio;polarization angle- 134
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Published：2023-04-14
Modern Applied Optics
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Monolithic optocoupler isolated driver chip
Abstract：In the power semiconductor market， insulated gate bipolar transistor （IGBT） and silicon carbide metal-oxide-semiconductor field-effect transistors （SiC MOSFETs） have excellent voltage resistance and frequency characteristics， and thus gradually replaced the traditional MOSFETs. The reliability design of IGBT and SiC MOSFET driver circuits is associated with rigorous challenges. Therefore， an optocoupler-isolated gate driver chip was designed in this study. Monolithic integration was realized by co-designing photodetectors and driver circuits. Silveraco software was used to simulate the photodetector. The simulation results indicate that the responsivity of the photodetector to 800 nm infrared light is 0.277 A/W， and the -3 dB bandwidth is approximately 90 MHz. Further， the optical structure of the optocoupler was optimized to effectively isolate the control end and the rear high-voltage drive circuit， and thus the crosstalk problem was addressed. The 0.18 μm 40 V bipolar-CMOS-DMOS （BCD） technique was used to tape out and test the package chip. The chip test results indicate that the chip propagation delay is only 98 ns when the input current of the light source is 10 mA， the chip power supply voltage is 12–40 V， and the input signal frequency is 20 kHz.Keywords：collaborative design;monolithic integration;optocoupler isolation;low delay- 123
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Published：2023-04-14 -
Effect of nanodiamond abrasive agglomeration on tribological properties of fused silica
Abstract：To investigate the effect of abrasive agglomeration on the wear behavior of optical glasses during magnetorheological finishing， this study used an environmentally controlled linear reciprocating tribometer to conduct friction and wear experiments of fused silica by rubbing against a stainless steel sphere and adding different degrees of agglomerated nanodiamond polishing solution. Optical microscopy and a white light interferometer were used to characterize the wear mechanism of the fused silica， and the tribological results were compared with those of actual magnetorheological polishing. Experimental results showed that the material removal rate （MRR） and subsurface damage of the fused silica increased with the degree of nanodiamond particle agglomeration. When the load was 0.5 N， the wear mechanism of the fused silica was domihnated by adhesive and abrasive wear， and no dissemble subsurface damage was found beneath the wear track of the fused silica. When the load was increased from 0.5 to 4 N， the wear mechanism of the fused silica was dominated by abrasive wear， and substantial surface and subsurface damage were found. Both the tribological experiments and magnetorheological polishing were conducted with polishing fluids having the same degree of abrasive particle agglomeration， and results showed that the MRR of the fused silica under the two methods was nearly the same. This indicated that the tribological test could be used to predict the MRR in actual magnetorheological polishing to a certain extent.Keywords：magnetorheological finishing;abrasive agglomeration;nanodiamond;fused silica;wear properties- 76
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Published：2023-04-14 -
Design of truss adjusting mechanism for secondary mirror of large aperture telescope
Abstract：In large-aperture telescopes， the relative positions of the primary and secondary mirrors must conform to stringent specifications. The secondary-mirror system is frequently designed as an adjustable mechanism with several degrees of freedom， owing to the high quality of the primary mirror. This significantly affects the telescope imaging. The secondary-mirror truss and adjustment mechanism are combined and designed to decrease the overall height of the telescope. Moreover， a secondary-mirror truss-adjustment mechanism that can be employed in large-diameter telescopes is designed. First， a detailed description of the designed adjustment mechanism is given， followed by static and modal analyses， and finally， a kinematic-performance test of the experimental prototype. The moving stroke of the designed mechanism in the Z direction can reach ±5 mm and the absolute positioning accuracy is better than 16 μm. The deflection stroke in the X/Y direction can reach ±0.574° and the absolute positioning accuracy is better than 6.4″. The mechanism complies with the itinerary requirements and secondary-mirror adjustment accuracy for large-diameter telescopes.Keywords：large aperture telescope;secondary mirror system;adjustment mechanism;support structure- 122
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Published：2023-04-14
Micro/Nano Technology and Fine Mechanics
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Sand-dust image enhancement using RGB color balance method
Abstract：This paper proposes a dusty image enhancement algorithm based on the RGB color balance method to address the problem of color difference in low-contrast and low-definition outdoor images in dusty environments. The method mainly includes two tasks： color correction and contrast enhancement. First， in view of the particularity of the color distribution of dust images and the illumination mechanism assumed by the gray world algorithm， an RGB color balance method （RGBCbm） that maintains the mean value of the color component is proposed such that the RGB three-channel component is stretched according to the mean value of the color component， which effectively removes the color curtain problem caused by dust in images. The multi-scale retinal enhancement algorithm with color restoration （MSRCR） is further used to improve the color correction results. Subsequently， the relative global histogram stretching （RGHS） method combined with the Lab color model is used to enhance and correct the contrast， color， and brightness of the image. Test results and verification of the proposed algorithm on experimental data show that the algorithm can effectively solve the color difference problem in various dust-degraded images and enhance the clarity of image details while improving the color richness and contrast of the image. In the quantitative comparison with other advanced algorithms， the highest underwater image quality measure （UIQM） and image contrast index （Conl） reach 0.602 and 0.994， respectively， which are 0.140 and 0.018 higher than those of other algorithms.Keywords：computer vision;Sand dust image enhancement;Color balance;color correction;multi-scale retinal enhancement algorithm with color restoration algorithm;elative global histogram stretching algorithm- 169
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Published：2023-04-14 -
Terahertz spectral features detection and accuracy identification of explosives in high humidity environment
Abstract：The fingerprint characteristics of the terahertz absorption spectrum of materials have been widely used in material identification， but the strong absorption of terahertz waves by water vapor in the actual atmospheric environment will cause the spectrum to oscillate severely； there will be increasing false， weak， and aliased peaks. These phenomena have seriously affected the accuracy of peak-finding comparison and the ability of substance identification. In spite of this， on the basis of extracting the terahertz absorption spectrum of explosives at relative humidity of 2%， 15%， 35%， 45%， and 60%， the continuous wavelet transform is expanded in the frequency domain to obtain a unique characteristic. Then， the network training is carried out on the frequency domain scale maps of explosives obtained under the above 5 different humidity conditions based on the deep learning method with the ResNet-50 network model as the basic network structure； the classification accuracy of the test can be up to 96.6%. To verify the effectiveness of the technology under untrained humidity samples， the time-domain signals of explosives at relative humidity of 50%， 55%， and 67% were fed into the identification system； the classification accuracy could reach 96.2%. Experiments show that a new terahertz material identification method， based on wavelet transform and ResNet-50 network classification training， greatly improves the accuracy of material identification in high humidity environment compared with the traditional peak-finding method. In addition， it avoids a series of complex preprocessing operations such as noise reduction and smoothing， and considerably expands the engineering adaptability of terahertz spectral detection technology. It provides help for accurate detection and identification of mines and other explosives in high humidity and extremely complex special operations environments such as mountains， forests， and depressions.Keywords：terahertz spectroscopy;high humidity environment;continuous wavelet transform;ResNet-50;classification and identification of explosives- 229
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Published：2023-04-14 -
Pneumonia aided diagnosis model based on dense dual-stream focused network
Abstract：X-ray images play an important role in the diagnosis of pneumonia disease， but they are susceptible to noise pollution during imaging， resulting in the imaging features of pneumonia being inconspicuous and an insufficient extraction of lesion features. A dense dual-stream focused network DDSF-Net is proposed in this paper for the development of an aided diagnosis model for pneumonia to address the abovementioned problems. The main steps of this method are as follows. First， a residual multi-scale block is designed， a multi-scale strategy is used to improve the adaptability of the network to different sizes of pneumonia lesions in medical images， and a residual connection is used to improve the efficiency of the network parameter transfer. Secondly， a dual-stream dense block is designed， a dense unit with a parallel structure for the global information stream and the local information stream is used， whereby the transformer learns global contextual semantic information. The convolutional layer performs local feature extraction， and a deep and shallow feature fusion of the two information streams is achieved using a dense connection. Finally， focus blocks with central attention operation and neighborhood interpolation operation are designed， background noise information is filtered by cropping the medical image size， and detailed features of lesions are enhanced by interpolating the medical images with magnification. In comparison with typical models used for a pneumonia X-ray dataset， the model introduced in this paper obtained better performance with a 98.12% accuracy， 98.83% precision， 99.29% recall， 98.71% F1， 97.71% AUC and 15729 s training time. Compared with DenseNet， ACC and AUC were improved by 4.89% and 4.69%， respectively. DDSF-Net effectively alleviates the problems of inconspicuous pneumonia imaging features and insufficient extraction of lesion features. The validity of this model and robustness of this paper are further verified by a heat map and three public datasets.Keywords：medical image processing;pneumonia X-ray images;dense network;residual multi-scale block;global and local information flow;focus block- 105
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Published：2023-04-14 -
Image fusion of dual-discriminator generative adversarial network and latent low-rank representation
Abstract：To improve the visual effect of infrared and visible image fusion， images from two different sources were decomposed into low-rank images and sparse images with noise removed by latent low-rank representation. Moreover， to obtain the fusion sparse plot， the KL transformation was used to determine the weights and weighted fusion of the sparse components. The generation adversarial network of the double discriminator was redesigned， and the low-rank component characteristics of the two sources were extracted as the inputs of the network through the VGG16 network. The fusion low-rank diagram was generated using the game of generator and discriminator. Finally， the fusion sparse image and the fusion low-rank image were superimposed to obtain the final fusion result. Experimental results showed that on the TNO dataset， compared with the five listed advanced methods， the five indicators of entropy， standard deviation， mutual information， sum of difference correlation， and multi-scale structural similarity increased by 2.43%， 4.68%， 2.29%， 2.24%， and 1.74%， respectively， when using the proposed method. For the RoadScene dataset， only two metrics， namely， the sum of the difference correlation and multi-scale structural similarity， were optimal. The other three metrics were second only to the GTF method. However， the image visualization effect was significantly better than the GTF method. Based on subjective evaluation and objective evaluation analysis， the proposed method can obtain high-quality fusion images， which has obvious advantages compared with the comparison method.Keywords：infrared image;visible image;latent low-rank representation;modified double-discriminator conditional generative adversarial network;image evaluation- 83
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Published：2023-04-14 -
Automatic extraction of red raspberry planting areas using time series multispectral images
Abstract：Raspberry has the reputation of being "the third generation of gold fruits." Obtaining accurate data on the planting area of raspberries is of great significance for adjusting the crop planting structure and industrial development in Shangzhi， the red raspberry country. Taking Zhoujiayingzi village， Weihe town， Shangzhi city， Heilongjiang province as the study area， a high spatial and temporal resolution of Sentinel-2 data was used to obtain time series data of the study area. Using time-series changes in terms of spectral characteristics and normalized vegetation index， the CART algorithm was used to estimate the raspberry planting area in the study area. A comparison with the results of planting areas obtained based only on multi-temporal remote sensing images was performed to explore any differences due to the participation of NDVI time-series data on the area extraction accuracy， and to compare the object-oriented classification and the support vector machine classification based on optimal time-phase data. The experimental results show that the two methods based on the time series CART algorithm obtain better results than the other two classification algorithms in extracting the planting area of raspberries and that they can obtain the planting area and spatial distribution of crops with a higher accuracy， which meets the needs of crop monitoring. NDVI time series data were then added to the multi-temporal data classification so that the spectral difference between crops could be enlarged， and the classification accuracy improved. Compared with only using Sentinel-2 multi-temporal data， the classification accuracy is improved by 1.67% and the Kappa coefficient is improved by 0.02.Keywords：multi-temporal remote sensing;subpixel Raspberry planting area;time-series data;sentinel-2;CART- 86
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Published：2023-04-14
Information Sciences
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