The fast tunability and reconfigurability are essential for a silicon photonic filter for various application scenarios, such as an optical filter, time delay, and wavelength division multiplexing.In this work, we propose a reconfigurable filter based on a self-coupled micro-ring resonator combined with three optical switches. By controlling the electrodes, the proposed component can be reconfigured into five different structures, including the optical switch, non-balanced Mach-Zehnder Interferometer(MZI) filter, dual-ring-coupled MZI filter, micro-ring resonator filter with a double injection, and a self-coupled micro-ring resonator assisted MZI filter.Simulations have been performed based on the transmission matrix of the proposed filter. Based on the simulation results, the reconfigured dual-ring-coupled MZI filter has the capability of switching from a notch filter to a bandpass filter with an extinction ratio larger than 35 dB. The micro-ring resonator filter with double injection can be switched between two different FSRs, and the frequency tuning range is approximately 18 GHz. Compared tonumerous integrated single-function optical filters, the proposed structure has much higher flexibility and reconfigurability, and has the potential to be applied in integrated optical signal processing and microwave photonic systems.

Shape sensing technology based on optical fibers is a new research direction in the field of optical fiber sensing. In recent years, fiber shape sensors have used several optical fibers with a specific spatial arrangement to measure the position and shape of the fiber or the connected objects. Because it is free from electromagnetic interference, easy to integrate, and has high accuracy in shape measurement, it can be applied to minimally invasive medical interventional catheter position tracking, critical structural shape measurement in the aerospace field, long-distance pipelines, and cable deformation monitoring. This paper discusses the application of fiber shape sensing technology in related fields. It systematically reviews the latest domestic and international research progress on this technology, as well as its key aspects. A detailed introduction is presented, and the major limiting factors and sources of errors in optical fiber shape sensing are summarized.

In this work, a two-laser-tracker system was developed, and its measuring and data processing methods were designed to precisely transmit coordinates in a limited space.First, two Leica AT402 laser trackers were modified, and two target seats were respectively installed on their handles to place spherical prisms. Thereafter, the height difference between the adapter center and instrument center was precisely calibrated as vertical eccentricity. Furthermore, the two laser trackers set up survey stations and aimed at the sphere prism on the handle of the other instrument. The observed values should be adjusted to the instrument centers considering the vertical eccentricity to obtain the aiming interaction observation between the instrument centers. Moreover, the two instruments measured the target points in the visible range. When the two laser trackers could observe sufficient common points, the common points and the aiming interaction observation could be used to transmit coordinates and orientation simultaneously. When there was no common point, the aiming interaction observation was utilized to transmit the coordinates and orientation. Measurement experiments were carried out in the engineering control network of the Shanghai Synchrotron Radiation Facility. The experimental results show that when there are enough sufficientpoints in adjacent stations, the accuracy of coordinate transmission can be improved using the aiming interaction observation. When there is no common point, at 9 m, the precision of transmitted coordinate accuracy is better than 0.22 mm, and the precision of the directional rotation angle is approximately 1″. This system can be applied to the measurement of a three-dimensional control network, and is especially suitable for precise coordinate transmission inpoor visibility conditions.

To realize the rapid and accurate measurement of a ball nut profile, a laser measurement method is proposed, and a measuring device is designed.First, a device to measure the nut profile is constructed based on the principle of a point laser reflected by a right-angle prism scanning along the axial direction. According to the mathematical model of raceway, a new data processing method of axial normal transformation is proposed. Furthermore, the translation and rotation errors of the right-angle prism, laser offset errors, and inclined laser errors are analyzed and calibrated. Finally, the outline of a standard steel ball and circular groove are measured by the designed frock,and the nut profile ismeasured.After error calibration, the measurement error of the point-laser scanning arc contour is less than 3.1 μm, and the standard deviation is less than 2.2 μm. The scanning image of the nut raceway is complete and useful, which meets the measurement requirements of the nut raceway profile.

To establish an effective and nondestructive subsurface defects detection technology, the fluorescence image technique of optics subsurface defect was studied. A small-aperture fluorescent defect-detection prototype was developed by systematically optimizing various parameters such as the excitation wavelength, imaging spectrum, imaging light path, and the detector. Based on the prototype, the surface and subsurface fluorescence defects of the finishing processing of fused silica and diamond fly-cutting processing KDP were characterized. The laser-induced damage threshold was measured by a 351-nm nanosecond pulsed laser. There is a significant difference in the subsurface defects of various samples, ranging from 0.012% to 1.1%. The relationship between the subsurface defects and the damage threshold was analyzed by statistical methods. The results show that the R2 value of the fused silica subsurface defect and the damage threshold curve is 0.907, and the R2 value of the KDP crystal subsurface defect and the damage threshold correlation curve is 0.947; both are strongly related. The results can be used to evaluate the processing quality of the optical components.Because of its nondestructive and short duration characteristics, the technique can be applied to the detection of full-area subsurface defects in large-dimension UV optical components, which makes it vital in engineering.

Reciprocating progressive scanning can improve the imaging speed and data utilization of confocal laser endomicroscopy.However, this scanning method can also create image distortion and dislocation, which affects the imaging quality of the system. In this study, the sampling time function during the anisochronous sampling process is deduced based on the movement rule of the galvanometric resonance scanner, and the horizontal distortion caused by speed changes in the galvanometric scanner is corrected. Moreover, the cross-correlation method is used to assess the degree of image dislocation. The genetic algorithm is used to obtain the optimal starting time of the sampling, which results in the correction of the image dislocation. Finally, the image distortion and dislocation are corrected by adjusting the sampling start time and time interval of the data acquisition.The confocal endomicroscopic imaging system based on reciprocating progressive scanning is established to verify the effects of correction of image distortion and dislocation. Experimental results show that this method can effectively correct image distortion and dislocation, and further improve the lateral resolution of images.Compared with existing methods, the local resolution of the image corrected by the method in this paper is improved from 10 pixel to 6 pixel.

Photoacoustic imaging is an emerging medical imaging technique combining the high contrast of optical imaging and the superior penetration depth of ultrasound imaging. It can provide detailed three-dimensional images of the feeding vessels of tumors, which is essential for the early diagnosis of cancer. In this study, we developed a transmissive coaxial photoacoustic digestive tract endoscopic imaging system using internal optical illumination and external ultrasonic detection. The phantom imaging results indicated that the transmissive system has a much better performance than the reflective non-coaxial system with a 43.3 dB higher Signal-to-Noise Ratio (SNR) and 28.4% better imaging depth. Ex vivo imaging results indicated that the transmissive system has a 9.7 dB higher SNR at a depth of 10.7 mm compared with the reflective system. The transmissive coaxial photoacoustic endoscopic imaging system, which exhibited a higher SNR and better imaging depth than the reflective system, shows that this design improves the detection sensitivity effectively. The significant improvements suggest that the developed photoacoustic endoscopy has great potential for translation into a broad range of clinical applications in gastroenterology.

Airflow disturbance can cause a change in the air refractive index, which will introduce an unknown wavefront measurement error, especially for large-aperture, long-focus optical systems. To suppress this effect, this paper proposes an indoor temperature field control method based on Computational Fluid Dynamics (CFD). First, the cause of the wavefront detection error induced by air disturbance is analyzed, and the feasibility of improving the uniformity of indoor temperature field and restraining the influence of air disturbance using active air supply is expounded based on hydrodynamics theory. Secondly, an indoor temperature field control method using fan array for active air supply is proposed through simulation modeling, which considers the composition of the self-collimation optical path of an off-axis Three-Mirror Anastigmatic (TMA) telescope (diameter of 500 mm, focal length of 6 000 mm) and the environmental conditions. Finally, the actual optical measurement data before and after temperature field control are compared to verify the effectiveness of the proposed method. The results show that the standard deviation among the seven groups of aberration coefficient measurements (mean values of multiple measurements over a period of time) decreased from 0.034λ to 0.005λ(λ=632.8 nm). The proposed method can effectively suppress the influence of airflow disturbance, which has certain reference significance for improving the optical detection accuracy of large-aperture long-focus optical systems under non-vacuum conditions.

For a Fast-Steering Mirror (FSM) driven by Voice Coil Motors (VCMs), the coil of the VCM touches the stator as the FSM achieves a broad range of motion. A novel FSM was developed to prevent the occurrence of undesired contact between the coil and stator. A compliant decoupling mechanism was designed to minimize the transverse displacement of the coil of the VCM. Moreover, for the FSM with a broad range of motion, the force-displacement relationship was nonlinear, which resulted in variable resonant frequencies at different motion positions. We developed a variable notch filter to eliminate the variable resonant modes, and a Proportional-Integral(PI) controller was designed to achieve closed-loop control. Compared to the fixed notch filter, the resonant frequencies of the variable notch filter were a function of the motion positions of the FSM. The bandwidth of the FSM was studied by finite-element analysis and experiments using fixed and variable notch filters. According to the experimental results, as a fixed notch filter was applied, the bandwidth of the FSM varied in different motion positions. When the motion position is less than 15.2 mrad, the bandwidths of the FSM along the θx and θy axes are approximately 95 Hz and 110 Hz, respectively; when the motion position is 18.2 mrad, the bandwidths of the θx and θy axes drop to 4792 Hz and 571 Hz, respectively. As a variable notch filter is applied, the bandwidths of the FSM along the θx and θy axes are stable at 95 Hz and 110 Hz, respectively; this result illustrates the need and effectiveness of applying a variable notch filter in an FSM system with a broad range of motion.

In order to predict online the subsurface damage depth of the specimen induced in grinding of hard-brittle material, a theoretical relationship between the cutting force of the diamond tool and the subsurface crack depth of the specimen was established. This relationship was based on the statistical analysis of abrasive height using probability and statistics. First, based on the indentation fracture mechanics of the hard-brittle materials, the intrinsic association between the propagation depth of the median crack and the indentation depth of a single abrasive was investigated. Subsequently, the number of actual abrasives located on the boundary of the tool end-face was calculated using mathematical statistics, and the internal correlation between the cutting force of the tool and the cutting depth of each single abrasive was developed. Finally, a method for quick online prediction of the subsurface damage depth was proposed (SSDmax=1284×SSDmaxtheo-3623), and its accuracy was verified by an actual grinding experiment of BK7 glass. The experimental results illustrate that this technique can achieve accurate online prediction of the depth of subsurface damage involved in the grinding process.

To achieve rapid, low-cost, and high-throughput detection of bacteria, an array flexible paper-based Surface-Enhanced Raman Scattering(SERS) detection chip was designed and fabricated. First, silver sol was prepared, and then the isolation area and the array detection area were constructed on paper base using the hydrophobicity of laser printing and carbon powder. Given the hydrophobic property of carbon powder, silver sol droplets were confined to the detection area. At a certain temperature, the silver sol dries naturally to form an array of active SERS detection chip. The paper-based SERS chip was characterized by Rhodamine 6G as probe molecule. The test results show that the detection limit of the chip is 10-8 mol/L, and the RSD of the repeatability test is about 11.85%. The SERS test of Escherichia coli(E. coli) shows that the chip can quickly obtain the Raman characteristic peaks of E. coli without labeling or complicated pretreatment. The advantages of the flexible paper-based SERS chip include simple structure, quick fabrication, and low cost. The array structure can realize simultaneous measurement of multiple parameters, and is expected to be used for direct and rapid detection of pathogenic bacteria.

In order to improve the accuracy of the 2RPU/UPR+RP over-constrained hybrid robot in practical application and meet the requirements of production practice, the error compensation research of the robot was carried out. Firstly, the motion principle of the over-constrained hybrid robot was introduced. Then, the geometric error sources that affect the end precision of the hybrid robot were analyzed, and the zero calibration and full calibration method for improving the accuracy of the hybrid robot were introduced. The hybrid robot was divided into the parallel mechanism and the swing head with single-degree-of-freedom. Theoretical research on zero calibration and full calibration were conducted on these two parts respectively. Then the calibration experiment system was built up based on the laser tracker, and true values of error parameters were obtained by using algorithm after calibration, which were compensated to the kinematics algorithm. The result, indicates that the proposed full calibration and zero calibration method can effectively improve the positioning accuracy of the hybrid robot.

In order to predict the temperature rise of the high speed motor in a Magnetically Suspended Control Moment Gyroscope(MSCMG) more accurately, it is necessary to calculate the eddy current loss of the motor winding and conduct thermal analysis of the MSCMG. In this paper, the maximum angular momentum of 200 N·m·s, rated speed of 12 000 r/min MSCMG was taken as the research object. Firstly, the principle of eddy current generation was analyzed. By combining analytical method and finite element method, the eddy current loss of high-speed motor winding was deduced and calculated. Then, a three-dimensional finite element model of the MSCMG was established, and the temperature distribution was obtained by thermal analysis on the basis of the known losses. Finally, a prototype temperature rise experiment was designed for verification. The simulation results show that the stator temperature is the highest and the stator winding temperature is 40.3 ℃. The motor stator temperature measured by the temperature rise experiment is 41.6 ℃, and the error is 3.1% compared with the theoretical value. Compared with the thermal analysis without considering eddy current loss, the accuracy is improved by 3.7%. It is more accurate to predict temperature rise by considering eddy current loss in thermal analysis. The work in this paper is of great significance to optimize the thermal design of MSCMG.

Considering the problem that the contact measurement influenced structure characteristics and the PID control parameter setting were not ideal in the vibration active control system, the machine vision technology was used to measure the vibration of the structure, and the vibration control was carried out with the PID optimized by artificial fish swarm algorithm. Rigid and flexible double-joint mechanical arm was selected as the research object. Firstly, the experimental platform was set up and the orthogonal test was designed to explore the vibration situation of rigid-flexible coupling mechanical arm and determine the motor setting parameters for subsequent vibration control; Secondly, CCD camera was used to capture the vibration image of the marker at the end of the mechanical arm, and the vibration displacement was obtained by processing and was used as the input of the control system. Finally, the artificial fish swarm algorithm was selected to optimize the PID parameters. The output signal of the controller was converted into control voltage by the output card. The control voltage was amplified by the power amplifier and drived the piezoelectric actuator to realize vibration control. The experimental results show that the average control effect of the optimized PID algorithm can reach 57.54% compared with the traditional PID control effect of 44.06%, which verifies the feasibility and superiority of the optimized PID control system based on visual vibration measurement.

Aiming at the difficulty of real-time control of 6-DOF redundantly actuated parallel mechanism, the coordinated relation of displacement input was studied for Stewart derivative topological configuration with analytical positive solution. Six low-coupling driving modes with different redundancy were realized by designing double composite spherical pair and convertible master-slave output prismatic pair. According to the scale constraints between the four positions on the moving platform, a forward kinematics algorithm with whole analytical solutions was constructed, and the correctness of the forward displacement solution model was verified. Six compatibility equations of displacement input were derived and simplified. The numerical solutions of the compatibility equations were obtained by using Newton-Raphson method and Broyden method respectively. The comparison results show that the computing time of Broyden method is about 78% of that of Newton-Raphson method and the accuracy of Newton-Raphson method is at least three times higher than that of Broyden method. The influence of various driving modes on the redundant coordination algorithm was studied from two aspects of admissible initial deviations and structural parameters. The results show that the redundant coordination algorithm has larger admissible initial deviations with the increase of the side length of the moving platform and the decrease of the initial length of the prismatic pair. Furthermore, introducing and defining the perturbation adaptive performance evaluation index based on interval analysis theory, the optimal redundancy of the mechanism is calculated to be 5 and the comprehensive perturbation adaptive performace of Broyden method is 1.27 times better than Newton-Raphson method. Finally, combined with the numerical performance, the three selection principles for the driving mode optimization of the Stewart derivative parallel mechanism is given. The research scheme can provide reference for structure model optimization and real-time control of 6-DOF redundantly actuated parallel mechanism.

At present, a new type of cloud track has emerged in China. Cloud track has the advantages of low cost, low energy consumption and short construction period. This new type of cloud track requires precise positioning of track detection. In order to eliminate the position error of cloud track detection, a new type of track detection vehicle was designed, and a new SIN-GPS positioning algorithm based on double-layer bidirectional LSTM network was developed. Firstly, the construction and sensor parameters of the track detection vehicle was inod uced. Then, the traditional SIN-GPS positioning algorithm and its shortcomings was analyzed. If GPS signal disappeared, the positioning error was very large. a bi-directional LSTM algorithm was proposed to illustrate the dynamic learning and compensation of errors when GPS signals disappeared. Finally, the accuracy of the algorithm in different motion states of the cloud track detection vehicle with three groups of experiments was analyzed. The results of experiments show that LSTM algorithm is superior to traditional algorithms and other intelligent algorithms. It reveals that the error of LSTM is 79.8% smaller than that of SINS when the vehicle is moving. The error of SINS is smallest when the vehicle is static. When setting the speed threshold of 0.2 m/s, using LSTM algorithm when it is larger than this threshold, and directly using SINS when it is smaller, the most accurate location results can be obtained.

Medical ultrasound image is an important basis for doctors to diagnose human tissue lesions. The speckle noise inherent in medical ultrasound images is easy to cause the destruction of texture information, which affects the doctor′s judgment on tissues and organs. Therefore, the denoising process of medical ultrasonic images has attracted much attention. In view of the limitation that the current medical ultrasound image denoising algorithm cannot maintain image texture, a fractional differential weighted guided filtering algorithm was proposed. Firstly, the speckle noise was converted into additive noise by logarithmic transformation. Combined with fractional differential algorithm, the texture factor was designed according to the correlation between pixel and edge texture, and the texture factor was used to improve the guided image filtering. Finally, the processing result of the medical ultrasound image was generated by the improved guided image filtering. In this paper, the ultrasound images of pig stomach and pig trachea were tested. Experimental results indicate that compared with the guided image filtering, the proposed method respectively gets 20.1% and 3.3% advancement for Structural Similarity Index Measurement and Cumulative Probability of Blur Detection. It can satisfy the proposed algorithm can effectively preserve the edge texture structure of the image while removing speckle noise.

Optical Coherence Tomography (OCT) has the characteristics of fast imaging speed and high resolution. It is widely used in the diagnosis of ophthalmic disease. In order to quickly obtain the depth information of the designated surgical area in ophthalmic surgery, this paper proposes a method of applying OCT to ophthalmic surgery navigation. Based on the swept-frequency OCT system, and the real-time observation is performed by a dichroic mirror combined with a CCD camera, and the coordinates of the scanning coordinate system and the camera coordinate system are matched. The scan positioning of the OCT is completed. For the error of image reconstruction and actual coordinates caused by the self-refraction of the sample, the OCT image reconstruction error correction is based on Fermat′s principle and Snell′s law, and the mapping relationship between the OCT image and the actual structure of the sample is theoretically derived. Experimental results indicate that the OCT image of a specific location can be acquired with a low error, and the OCT image information can be corrected accordingly. The system is capable of measuring accurate information on the location of the sample.

In order to alleviate the pressure of subsequent data acquisition and processing systems caused by high data volume in Frequency Domain Optical Coherence Tomography (FD-OCT), and to address the contradiction between imaging time and imaging quality, we introduced compressed sensing technology and focus on the reconstruction algorithm in this technology. First, we analyzed the framework of the compressed sensing technology, the frequency domain OCT image was sparsely represented by Discrete Cosine Transform. Next, we used Gaussian random matrices to perform linear observations on OCT images. Then, we studied the principle of FOCUSS (Focal Underdetermined System Solver) reconstruction algorithm, and combined the block idea, introduced the regular term lp norm and embed anisotropic smoothing operator in the algorithm. Finally, we combined all the small image blocks to obtain the compressed sensing reconstruction result of the whole frequency domain OCT image. Experimental results indicate that the running time of the improved reconstruction algorithm is shortened from 78.65 s to 1.89 s, and the image block effect is significantly improved, the PSNR value of the reconstructed image is improved by 1.6-2.7 dB, and the SSIM value can reach 0.938 3. Compressed sensing technology can accurately reconstruct the original frequency domain OCT image with a small amount of sampled data. The improved FOCUSS reconstruction algorithm can achieve the balance of frequency domain OCT image reconstruction efficiency and reconstruction quality to some extent.

The traditional segmentation algorithms for straw coverage detection basing on thresholds or texture features were difficult to get rid of the disadvantages of low accuracy, high complexity and time-consuming, and the effect of segmentation on complex farmland scenes containing a lot of interference factors was not good. Therefore, this paper proposed a semantic segmentation algorithm (DSRA-UNet) with high accuracy, a small mount of training parameters and high running speed. Combined with UNet′s symmetric codec architecture, this algorithm used standard convolution in shallow feature maps, and depthwise separable convolution in deep ones. Residual structure was built in each layer to increase the network depth,which can reduce the number of parameters and improve the accuracy at the same time. In addition, the global maximum pooling attention mechanism was added during the skip connection process to further improve the segmentation accuracy of the network. The algorithm was verified on the straw datasets, and the experiment results showed that the mean of intersection over union reached to 94.3% in the proposed algorithm of this paper. The number of training parameters of the algorithm was only 0.76 M, and the test time of single picture was less than 0.05 s. The algorithm could accurately segment the straw and soil, and separate the interference information in the complex environment, especially solving the shadow problem in image.

3D positioning of physical body points plays an important role in machine vision applications involving feature extractions, pattern recognition, geometrical measurement and motion analysis. To cover a wide detection and mitigate the influence of occlusion some multiple view technique for positioning is adopted, a technique that is generally fulfilled using expensive instruments and specialized software and thus its applications are restricted in terms of number of points that can be positioned simultaneously, ability for user programming and affordability. With both complete algorithm and procedure, this paper proposed a DLT(Direct Linear Transformation)-based method for 3D positioning of object point in the world coordinate frame via multiple view geometry, applicable to multiple view provided by either a single camera moving into different positions for still scene positioning, or by multiple cameras for a dynamic positioning application. This method consisted of 2 main steps, i.e. a DLT-based camera calibration and a 3D coordinates reconstruction (positioning) with the camera parameters obtained in calibration. In the calibration step, a minimum of 6 control points, not co-planar but with known world coordinates, were set up and linear equations were formulated modeling relationship between world frame coordinates of these control points and their relevant image points′ position in the camera coordinate frame, and equations then were solved via least squares method for best linear estimation of the camera parameters in the form of a series of L intermediary parameters. In the positioning step, the concept of finding intersection point of multiple spatial ray-each ray emanating formed the corresponding camera′s optical center and the image point corresponding to the same physical point-was used to formulate equations for the 3D positioning, which than were solved also via the linear least square method with the obtained L parameters. Still scene physical point positioning tests of 10 control points and 20 test points were conducted on a field leveler machine platform, where the scene was captured by one camera in 3 different positions and true reference positions of the test points provided by a total station. Results show that the average absolute error of the coordinates measured in the X, Y and Z directions is 4.19 mm, 3.97 mm, 3.69 mm, and the spatial relative distance error is 0.81%, thus satisfying the needs of general geometrical measurement. The method proposed can measure static and dynamic 3D world coordinates for multiple physical points, though higher via a more complicated DLT-based calibration procedure for the additional cameras′ distortion parameters.

Aiming at the difficulty of multi-scale detection of ship targets in infrared polarization images under complex interference conditions of sea-sky scene, a ship target detection method was proposed based on guided filtering and adaptive scale local contrast method. First, by using the intensity information as the guiding information to guide and filter the infrared polarization image obtained the fusion image with higher local contrast and local signal-to-clutter ratio. Then, based on the vertical gradient characteristics of the fusion image, detecting the sea-sky line method was proposed so that sea-sky line weighting suppressed the sea clutter on the fused image. Finally, based on the single-scale local contrast method and the ship target proportional feature, the adaptive scale local contrast method was proposed. When the scale matched the target, the response was the largest, and the maximum scale was determined by the response of the target at different scales. The experimental results show that the local contrast and local signal-to-noise ratio of the image are improved by the guided filtering fusion method. Compared with the typical detection methods, our method can effectively suppress interference and detect different scales of ship targets in sea-sky scene with high robustness and accuracy. The detection accuracy ratio and false alarm ratio are 95.0% and 3.5%, respectively, which provides a new method for infrared polarization image target detection.

Aiming at the problem of camera drift and low-quality reconstruction caused by accumulated errors in pose estimation for large-scale reconstruction, we proposed a method to reduce accumulated errors. First, based on the model fused by the latest K depth and color images, the geometric and photometric error of the input RGB-D image were minimized to track the camera. Then, if the distance between the camera position and the subvolume center was more than a given threshold, the subvolume was shifted by multiples of voxel size, the camera was continuously tracked and the local scene model was reconstructed based on the newly created subvolume. Finally, the corresponding surface points were searched by the iterative step method between subvolumes, and the global camera trajectory was optimized by Euclidean distance and photometric error between the correspondence. The experimental results based on the dataset show that the camera pose estimation accuracy is improved by 14.1% than the current method, and the global trajectory optimization accuracy is improved by 8%. The system designed in this paper can also reduce the accumulated errors in pose estimation and reconstruct a high-quality scene model for self-collected data.

To remove the Poisson noise from the X-ray images, in this paper, it was proposed that noise was reduced by using Nonlinear Principal Component Analysis (NLPCA) from the X-ray image sequence. At first, an X-ray image sequence was sampled and the Poisson noise in images was converted into Gaussian noise through Anscombe transform; every noisy image was regarded as a combination of the noise components and the signal component, and then NLPCA was used to separate the signal component from the noise components to reduce noise; the final denoised image was obtained by using Anscombe inverse transform. The results show that, when the number of noisy images in the sequence increases from 2 to 50, the proposed denoising method increases the noisy Shepp-Logan image′s PSNR value from 28.289 4 dB to 37.267 8 dB and increases the SSIM value from 0.700 7 to 0.963 8. Compared with other denoising methods, the proposed denoising method can preserve more image details while reducing the Poisson noise.

In the three-dimensional (3D) precision measurement of large component, the detection accuracy of cooperative targets is low due to complex structure of large components and various measurement environment. To solve this problem, a multi-type cooperative target detection method using improved YOLOv2 convolutional neural network was proposed. Firstly, the data augmentation method combined with WGAN-GP was employed to amplify the number of cooperative target images. Secondly, the convolutional layer dense connection was used instead of the YOLOv2 basic network layer-by-layer connection to enhance image feature information flow, and the spatial pyramid pooled was introduced to convergence image local area feature. Base on those two parts, the multi-type cooperative targets detection method with improved YOLOv2 convolutional neural network was constructed. Finally, the multi-type cooperative targets detection model with improved YOLOv2 convolutional neural network was trained by the augmentation dataset for detecting the multi-type cooperative targets. The experimental results of multi-type cooperative target detection indicate that, detection precision of the proposed method is up to 90.48%, and detection speed is 58.7 frame per second by using image dataset of multi-type cooperative targets to test. This method has higher precision, rapid speed and strong robustness, which can satisfy the multi-type cooperation targets′ detection requirements for 3D precision measurement of the large component.