The influence of atmospheric turbulence on wireless optical communication systems cannot be ignored. In order to accurately reflect the actual features of laboratory-simulated multiple-input multiple-output (MIMO) atmospheric turbulence channels, a method using phase screens to simulate MIMO atmospheric turbulence channels was proposed. The liquid crystal modulation method based on liquid crystal spatial light modulator (LC-SLM) was studied, and the feasibility of the method was verified by experiments. The experimental results show that the laser spot of MIMO atmospheric turbulence channels simulated by phase screen has different degrees of distortion. In the turbulent environment, the power stability of the two-channel laser emission system is better than that of the single-channel laser emission system. Under the forward error correction error limit (3.8×10-3), the link penalty of the single-emission single-receiving system is 10.5 dB, and the link penalty of the two-emission two-receiving MIMO system is 9.3 dB. This research provides a new idea for the experimental method of simulating MIMO atmospheric turbulent channels in laboratory.

A high-sensitivity temperature sensor based on dual-core fiber coupling effect and vernier effect was proposed. The sensor was composed of two fibers which with a certain length difference, they were dual-core photonic crystal fiber and single mode fiber. The vernier effect was achieved by dual-core photonic crystal fiber through the cascade, and in the meantime the temperature sensing was achieved by filling the pores with ethanol in the middle of the fiber core. The simulation results show that the average temperature sensitivity of -20.37 nm/℃ of the temperature sensor can be achieved in the temperature range of 35℃~45℃. Compared with the sensor which only depends on the energy coupling effect of dual-core photonic crystal fiber, the temperature detection sensitivity of the proposed sensor is 10 times higher.

In the manufacturing technology of additive materials, the characterization of dendrites is crucial for analyzing the mechanical properties of laser cladding layer. However, the labeling of the dendrites is mainly completed manually at present, which is time-consuming and easy to introduce artificial errors, while the deep learning can improve the accuracy of target recognition. Based on the U-net network, the BNC-Unet network which was suitable for the identification and segmentation of dendrites was proposed. The serial attention mechanism and the Batch Normalization layer were effectively deployed in the upsampling and downsampling regions to adjust the weight information of image features. The intersection over union (IoU) was selected as the evaluation index of the segmentation results, and the results of original U-net network and different improved methods under this index were compared. In the test set, the segmentation accuracy index of BNC-Unet network for dendrites is 84.2%, which is 8.97% higher than the results of original U-net network. The index shows that the BNC-Unet network can accurately identify the morphology of dendrites from metallographic diagrams of laser cladding layer, and the accuracy of dendrites identification is significantly improved, which is convenient for evaluating the properties of cladding layer after the laser cladding test.

Aiming at the problem of periodic arch protrusion in laser-induced breakdown spectroscopy (LIBS) data, an improved baseline correction algorithm was proposed. By adjusting the local penalty coefficients, the algorithm which was based on penalized least square method could not only fit the periodic arch protrusion, but also reduce the effect of spectral lines intensity on fitting baseline. Compared with other baseline correction methods, the root-mean-square error (RMSE) of the proposed algorithm was smaller when fitting the simulation baseline, and the correlation coefficients of the calibration curve based on spectral data obtained by the proposed algorithm reached 0.997 2. The results show that compared with the existing baseline removal method, the proposed algorithm can better retain the effective information of the spectral data when the echelle grating spectrometer collecting the baseline of LIBS.

Due to the existence of image motion, the imaging resolution of aerial photoelectric imaging system decreases, which seriously affects the overall performance of aerial photoelectric system. The image motion compensation technology can be used to improve the imaging quality of aerial photoelectric system. The principles of image motion compensation technology for mobile detectors and moving optical elements were analyzed, with emphasis on the high-precision image motion compensation technology based on fast steering mirror (FSM). Through the simplified engineering analysis, the law of follow-up angle of image motion compensation of FSM in parallel optical path and converging optical path was deduced, respectively. In addition, the defocus distance caused by the FSM in the converging optical path were analyzed, and the influence of defocus distance on the wave aberration of the optical system was discussed. The simulation results show that the wave aberration increases linearly with the increase of defocus distance. By analyzing the influence of wave aberration of optical system on its optical modulation transfer function (MTF), the results show that the F number is equal to 8, and at the Nyquist frequency, when the defocus distance is less than 0.1 mm, the declining quantity of optical MTF is within 26.6%.

When the traditional key frame extraction algorithm is applied to the theodolite image sequence, a large number of unstable tracking image frames will be extracted. In order to better retain the stable tracking measurement information of the target, after analyzing the characteristics of the theodolite image sequence, a key frame extraction algorithm for the theodolite image sequence based on the local maximum was constructed. Firstly, the frame difference of the image sequence was calculated by the algorithm. Then, the Hanning window function was used to smooth the frame difference. Finally, based on the smoothed local maximum of frame difference, the key frame was extracted. The experimental results show that the proposed algorithm can better retain the tracking measurement information of the target compared with the traditional frame difference intensity sorting method. The extracted key frames are more uniformly distributed in the entire tracking measurement image sequence, and the scene information contained is more abundant.

The patch-match algorithm has been widely used in binocular stereo reconstruction due to its low memory consumption and high reconstruction accuracy. However, the traditional patch-match algorithm needs to iteratively calculate the optimal disparity d for each pixel of image in an orderly manner, which resulting in a high running time. In order to solve this problem, a learning-based model on the basis of traditional patch-match algorithm as a guide to reduce the running time and improve the accuracy of stereo reconstruction was introduced. First, the deep learning model was used to output the initial disparity map of each pixel with heteroscedastic uncertainty, which was used to measure the accuracy of the disparity predicted by the network model. Then, the heteroscedastic uncertainty and initial disparity were taken as the prior information of patch-match algorithm. Finally, in the plane refinement step, the heteroscedastic uncertainty of each pixel was used to dynamically adjust its search interval to achieve the goal of reducing the running time. On the Middlebury dataset, compared with the original algorithm, the running time of the improved algorithm is reduced by 20%, and the reconstruction accuracy of the discontinuous region is slightly improved.

Aiming at the problems that the traditional visual background extractor (ViBe) algorithm cannot reflect the scene changes in time and has poor adaptability to dynamic scenes, an improved ViBe algorithm was proposed by using randomly selected background samples and 24 neighborhood method to obtain the initial background, which could accelerate the "ghost" ablation. The average adaptive threshold calculation method was adopted to improve algorithm adaptability to external dynamic environment and illumination changes in combination with OTSU method and uniformity measurement method, which retained effective pixels to the greatest extent. In the update phase, the adaptive update factor was introduced, which could effectively reduce the misjudgment probability, so as to enhance algorithm robustness. Finally, the target was more complete through morphological processing and filtering. The standard dataset video was applied to test and compare the improved algorithm. Compared with kernel density estimation (KDE) algorithm, Gaussian mixed model (GMM) algorithm and traditional ViBe algorithm, the indexes of the improved algorithm were greatly improved. The accuracy is improved by 30.44%, 40.72% and 20.95%, respectively and the percentage of wrong classifications is reduced by 43.28%, 40.59% and 29.43%, respectively.

Due to the complex indoor environment, the visible light location awareness based on Elman neural network has the problems of slow convergence speed and low positioning accuracy. An optimized Elman neural network based on sparrow search algorithm (SSA) was proposed, and a visible light indoor location awareness algorithm was fused with K-means clustering. The database was established for the collected data, the topological structure and connection weight threshold of the Elman were optimized by using SSA, and the training model was designed, so as to solve the problem that the indoor location awareness algorithm based on Elman neural network was easy to fall into the local optimization and improve the convergence speed and robustness. The K-means was used to optimize the classification of database, and the processed data was substituted into the model training to obtain the preliminary prediction results. The preliminary prediction results were substituted into the subclass for secondary training to obtain the final coordinates of predicted position, which further improved the positioning accuracy. The experiment based on three-dimensional space of 0.8 m $ \times $0.8 m $ \times $0.8 m was carried out, and the results show that the average positioning error of the proposed algorithm is 3.22 cm, and the probability of positioning error less than 6 cm is 90%, which improves the positioning accuracy by 7.5% compared with the SSA-Elman algorithm and by 16% compared with the Elman network algorithm.

Based on the application research of 3D laser scanning technology in railway tank car, the problems of incomplete point cloud and noise which were found during the scanning process were analyzed, and a fast and effective optimized processing method of point cloud was proposed. The new method included sp-H point cloud pre-processing method and Eti-G modeling optimization key algorithm. The verification test results show that the new optimized processing method of point cloud can be used to optimize the noise and incomplete point cloud in a relatively short time and can fast and efficiently reconstruct the model, which improve the applicability of scanning the point cloud under different working conditions, and the efficiency and accuracy of scanning work are also promoted. The related expanded uncertainty of volume measurement results of railway tank car reaches 2.4×10-3, which is the highest accuracy level of railway tank car volume scanning, and provides some references for the development of 3D laser scanning technology.

The fast circumferential scanning detection system is a new panoramic photoelectric system which realizes the gaze compensation imaging of single field of view scene by using inverse scanning device with high-speed swing. The fast scanning principle of the system was introduced in detail, which pointed out that the high-precision stability control of scanning platform was the key factor to the design and implementation of fast circumferential scanning detection system. According to the control mechanism of scanning platform, the mathematical models of horizontal and vertical inertial stabilization platform were established, the control of scanning platform by adopting fractional-order proportion integration differentiation (PID) controller was realized, and finally, the control performance of scanning platform based on fractional-order PID control algorithm was analyzed and verified. The experimental results show that the scanning platform using fractional-order PID controller has the advantages of no overshoot and stronger anti-disturbance performance in comparison with traditional PID controllers. The horizontal stabilization accuracy is improved from 0.005 82°(1 $ \sigma $) to 0.001 26°(1 $ \sigma $), and the vertical stabilization accuracy is improved from 0.003 66°(1 $ \sigma $) to 0.001 62°(1 $ \sigma $), which can ensure the described fast circumferential scanning detection system to obtain the clear and stable panoramic images.

In order to solve the problems of short reference working distance and small measuring range of laser displacement sensors developed independently in China at present, an imaging optical system for a wide-range laser displacement sensor was designed, which was suitable for the long distance measurement. Based on the laser triangulation principle, combined with specific application requirements, the performance indicators of a wide-range laser displacement sensor and parameters of an imaging optical system were calculated. The five-piece lens structure was selected as the initial structure of the system, and the imaging optical system of wide-range laser displacement sensor was designed with optical design software. The optimal design and performance analysis of the system were completed, and the system with reference working distance of 1 000 mm, measuring range of ±500 mm and resolution of 0.4 mm was developed. The simulation results show that the system can achieve good imaging quality within the measuring range of ±500 mm. The proposed laser displacement sensor imaging system has the advantages of long working distance, wide measuring range and simple structure, which can meet the requirements of wide-range measurement at 1 000 mm.

The imaging circle of panoramic fisheye optical system is usually a complete circle, which is smaller than the vertical size of the sensor. Compared with rectangular sensor, the area of circular imaging circle is smaller and the utilization rate of effective pixels of sensor is low. Combined with the characteristic that the imaging circle of panoramic fisheye optical system is smaller than that of sensor, a panoramic fisheye optical system based on freeform surface design was introduced, which could realize elliptical imaging area and greatly improve the utilization rate of effective pixels of sensor. The freeform surface model was built by using the optical design software, which was composed of glass lens and plastic lens. The imaging area of the asymmetric panoramic fisheye optical system was designed to be ellipse by eliminating aberration and controlling the focus shift under different temperature fields. The X direction of the lens image height was close to the horizontal size of the sensor, and the Y direction of the lens image height was close to the vertical size of the sensor. Without considering the manufacturing tolerance, according to the circle and ellipse area formula, for sensor of 4:3, the effective utilization rate of sensor pixels in the circular imaging area was about 58.9%, and that in the elliptical imaging area was about 78.5%. Finally, the simulation and calculation results show that the utilization rate of effective pixels of the sensor with elliptical imaging optical design is about 15% higher than that with circular imaging optical design.

In order to realize the optical beam transmission with approximately equal optical path for a certain distance in space, a newly-designed wavefront shaping system with off-axis ellipsoidal reflector was proposed. On the basis of the geometric optics and primary aberration theory, the influences of conic coefficients and off-axis amounts of the ellipsoidal reflector on the optical path difference of the image plane were analyzed in optical design software Zemax, the wavefront shaping systems of two kinds of optical structures of planar-ellipsoidal reflector and double ellipsoidal reflector were designed, and the tolerances of the two structures were compared. The analysis results show that both the planar-ellipsoidal reflective system and the double ellipsoidal reflective system realize the optical beam transmission at a distance of 1 m in space, and the optical path difference between each field of view pupil is 0.14 mm and 0.04 mm, respectively, under the condition of 3 mm object height field of view and aperture angle of 6°. Therefore, the shaping effect of the double ellipsoidal reflective structure is better than that of the planar-ellipsoidal reflective system, but the double ellipsoidal reflective structure is more sensitive to the tolerances.

The terahertz pulse signal has the characteristics of "fingerprint spectrum" in the frequency domain, which can be used for qualitative analysis of substances. A secondary aspheric TPX plano-convex lens was designed to improve the ability of lens to focus on the terahertz beams, with the help of optical analysis and optimization functions of Zemax software. The terahertz beam shaping optical system was designed by using the plano-convex lens, and the optical system was used in a terahertz time-domain spectroscopy system. The terahertz spectroscopy tests were performed on moxifloxacin hydrochloride and levofloxacin, and the absorption coefficient and refractive index curve in frequency domain were obtained after algorithm processing. The test results show that the refractive index of levofloxacin is higher than that of moxifloxacin hydrochloride in the range of 0.1 THz~3.5 THz band, but the change of the refractive index of moxifloxacin hydrochloride is more gentle than that of levofloxacin. The moxifloxacin hydrochloride has obvious absorption peaks at 1.03 THz, 1.92 THz, 2.58 THz and 2.84 THz, and the levofloxacin has obvious absorption peaks at 1.35 THz, 1.96 THz, 2.52 THz, 2.73 THz.

An optical system of a spectrometer based on the double Rowland circle optical structure and its related design methods were proposed. The optical path in the detection wavelength range of 200 nm~500 nm was a conventional Rowland circle optical structure. The optical path in the detection wavelength range of 500 nm~700 nm used the zeroth diffraction order subspectral lines diffracted by a concave grating, which were adjusted by a plane reflector to project the spectral lines into another concave grating, and the double Rowland circle optical structure was realized. According to the design requirements and the mutual constraints among the various parameters of the optical system, the various parameters were designed and calculated. Based on Zemax simulation analysis, the optical parameters were adjusted and the feasibility of the optical system was verified. Aiming at the problem of aberration of the planar signal detector on the Rowland circle, the reflector was used to increase the number of signal detectors, and the aberration was reduced by 4.475 μm compared with that of initial structure. The overall optical structure size of the spectrometer was less than 400 mm 500 mm. Simulation results show that the spectral band range measured by the spectrometer can reach 200 nm~700 nm, and the whole band resolution can reach 0.4 nm.

The reflection and refraction of light are the most basic methods for the application of geometric optics. In the processing of modern precision optical elements, the different expression methods can provide different solutions for light tracing, prism error analysis as well as prism assembly and adjustment. The traditional form expression methods of the law of reflection and the law of refraction of light were introduced, and the expression methods of vector, matrix and quaternion were derived. Through the simulation calculation assisted by Matlab, the reflected rays of incident light in two different areas of the Schmidt prism inspection optical path was symmetrically distributed on both sides of the reflected rays on the front surface in the horizontal direction, which was consistent with the practical application. The application of expression methods of vector, matrix and quaternion in Schmidt prism inspection optical path was realized. The three expression methods can provide scientific and practical solutions for light tracing, prism error analysis as well as prism assembly and adjustment.

In recent years, the magneto-rheological polishing as a deterministic processing method has become an essential way to obtain the high-precision aspheric surfaces. Take the rotationally symmetric secondary paraboloid as an example, the theoretical method of using the polishing wheel to calibrate the workpiece position in magneto-rheological polishing was analyzed, and the experimental verification was carried out on a Φ 230 mm fused quartz workpiece. The workpiece position was calibrated with less than 3 times of adjustment in the X direction and Y direction, respectively, and the offset in both X direction and Y direction was lower than 0.009 mm, respectively. The surface polishing experiment was conducted by magneto-rheological polishing technology on the workpiece, and the root-mean-square (RMS) of surface shape was converged from λ/7 to λ/40 after processing. The experimental results show that the proposed tooling calibration method of aspheric workpiece position is simple and reliable, which can accurately locate the workpiece and conducive to magneto-rheological polishing processing for high-precision aspheric surface.

In order to improve the illumination uniformity of the light emitting diode (LED) light source array, an improved particle swarm algorithm and a new arithmetic LED array arrangement method were proposed. According to the illumination distribution model, the illumination uniformity evaluation function of the illuminated surface was established, and the improved particle swarm algorithm was used to optimize the new arithmetic, rectangular and circular LED arrays. The data of the optimized LED array was imported into the optical software TracePro for simulation and verification, and the illumination uniformity of the optimized arithmetic, rectangular and circular LED arrays was 82.89%, 73.31% and 78.56%, respectively, which was 15.84%, 10.65%, and 15.57% higher than the illumination uniformity of the LED array before optimization. The research results show that the improved particle swarm algorithm has faster convergence speed and higher convergence accuracy, and the proposed new arithmetic LED array has better illumination uniformity.

The high-risk pathogenic microorganisms in the air pose a great threat to human society, but the traditional monitoring methods cannot accurately identify and classify the microorganisms in the air. Therefore, based on the principle of laser-induced fluorescence technology and single photon detector as the core device, an efficient fluorescence spectrometer was designed and built for the identification and classification of high-risk pathogenic microorganisms in the air, and the spectrometer could predict the concentration of microorganisms, which was of great significance to environmental safety. For the data collected by the spectrometer, the two input forms of one-dimensional vector and two-dimensional matrix were used to realize the identification and classification of fluorescence spectra, and the identification and classification effects of deep learning networks such as principal component analysis network, convolutional neural network and full convolutional network were studied and compared. The experimental results show that the identification and classification accuracy of convolutional neural network model with matrix input reaches 98.05% in the test set, and the prediction accuracy of microorganisms concentration of full convolutional network model with matrix input reaches 98.97% in the test set.

Aiming at the problems of low efficiency, high cost and poor accuracy in existing methods in aviation fastener sorting process, a rotation target detection method for intelligent optical perception with edge computing was proposed. To further improve the performance of the target detection model, a feature fusion mechanism based on enhanced semantics and optimized space was constructed. A type of dilated ghost module to lower the parameter quantity of the feature fusion network was designed, and enable the edge computing deployment in industrial scenes. Using the Gaussian-like circular smooth label method, the rotation target detection was realized on the prediction branch of the model detection layer, which significantly enhanced model detection performance and was more favorable for automated grasping of industrial robots. The detection accuracy on the authoritative public rotation dataset reached 77.16%. Finally, the proposed detection method was implemented in an embedded intelligent device. The edge computing deployment shows that the total accuracy reaches 99.76%, and the inference speed is more than 20 frames per second (FPS), which is sufficient for industrial applications.

In order to design and manufacture integrating sphere radiation sources with high angular uniformity, it is necessary to provide optimized design parameters. Based on the radiative transfer theory of cavity, a simulation model of light exitance distribution of light-emitting unit based on cascaded integrating sphere structure was established, and the relationship between the installation position of the Lambertian light-emitting unit and the angular uniformity of the cascaded integrating sphere radiation source was obtained. The simulation results showed that, in ideal conditions, when two Lambertian cascaded sub-spheres were used as light-emitting units and were symmetrically installed at an angle of 10° with the normal direction of the light outlet of the cascaded integrating sphere radiation source, the angular uniformity in the observation area at an angle of ±20° between the center of the sphere and the normal direction of the light outlet could reach the level of 0.03%. Finally, the angular uniformity of the cascaded integrating sphere radiation source at the 30° angle position of the cascaded sub-spheres was measured experimentally, and the experimental results were close to the simulation results. Therefore, by optimizing the type and installation position of the light-emitting unit, the angular uniformity of the integrating sphere radiation source could be effectively improved.

A laser energy meter was designed to meet the requirements of laser energy measurement with wide band, high precision and large energy range. The fast-responding thermopile was used as the sensor, and the high-absorptivity carbon nanolene material was coated on the detection surface of thermopile, which realized the wide spectrum absorption. The energy meter had an ultra-wide energy range of 1 mJ~40 J and the high measurement accuracy by using two thermopile detectors arranged on the both sides of the energy meter. The three-dimensional finite element model of the thermal path structure of absorption cavity was established by using the finite element simulation software, and the heating model of different types of laser pulse were simulated. According to the simulation results, the linearity of the detector was corrected, thus the measurement error caused by the nonlinearity between the output electrical signal of the sensor and the measured optical signal was reduced. The calibration experiment of the energy meter was carried out with the standard device of laser energy meter. The measurement results show that the repeatability of the modified laser energy meter is 0.6%, and the linearity is better than 1.1%. The laser energy meter is traceable to the national laser energy benchmark, and the relative extended uncertainty of measurement reaches an excellent level of 2.5% (k=2).

In order to monitor the dust concentration of particle materials in the process of handling and transportation online in real time and improve the accuracy and reliability of dust concentration measurement results, an improved dust concentration measurement algorithm based on the eigenvalue calculation of image transmittance was proposed. First, the experimental platform of vision measurement of dust concentration was established, and the dust images were collected. Then, the characteristics of transmittance of dust images were extracted. Based on the dark channel theory, the image transmittance of dust images was calculated by combining the information of image saturation and image brightness. Finally, the mapping relationship between dust concentration and image transmittance was established by the polynomial fitting method. And the high-efficiency and high-precision measurement of dust concentration was realized. The research results show that the proposed algorithm can not only effectively measure the dust concentration, but also the average relative error is only 7.77%. The accuracy is effectively improved and the measurement range is further expanded.

When the metal surface profile is measured by the linear structured light method, the extraction error of stripe center is often large due to the influence of optical properties and speckle noise of metal surface. Therefore, a profile measurement method that used incoherent linear structured light was proposed, which could avoid the influence of speckle noise. A corresponding method for extracting the center of incoherent linear structured light stripe was proposed by analyzing the characteristics of metal surface profile stripe images. Firstly, the original stripe image was segmented using adaptive threshold segmentation algorithm combined with integral image principle. Then, the center coordinates of original stripe were roughly extracted by gray centroid method. The regions of interest and background of stripe image after threshold segmentation were determined by extending the roughly center to stripe width direction, and the noise in the background region was removed. Finally, the stripe center was extracted by geometric center method after median filtering. The experimental results show that the average error of incoherent light stripe center of roughness specimen surface extracted by proposed method was 1.5 μm and that of involute gear was 0.9 μm, which are both smaller than those of line laser stripes. The proposed method can accurately extract the center of incoherent linear structured light stripe on metal surface.

The plasma processing technology is an advanced optics fabrication technology developed in recent years, which has the advantages of quickly mitigating or removing surface/subsurface damage caused by traditional optics fabrication methods, and trimming optical surfaces with high efficiency, high precision and high resolution. Starting from the basic principle of plasma optical processing, the generator was briefly introduced based on the excitation frequency and characteristics of the plasma. The research contents and achievements of key technologies such as jet characteristics, interface physicochemical reaction, damage removal mechanism, removal function, processing thermal effect and process positioning involved in plasma processing technology by various research institutions were analyzed, and the new optical processing technology of plasma was introduced. With the continuous deepening of research, a plasma processing model under the combined action of multi-physics field and chemical reactions was constructed to reveal the intrinsic relationship between the distribution of surface plasma characteristics and the removal function, so as to establish an accurate removal function model, which is the development direction of improving the modification accuracy. The research on thermal effect control methods and compensation strategies plays an important role in reducing the modification error caused by thermal effects.