摘要:In order to improve and optimize the traditional symmetrical design of progressive addition lenses, there were problems such as blind angle and distortion of the field of view. Two offset methods based on a rotation translation algorithm and an interpolation algorithm were proposed. Firstly, the binocular convergence phenomenon of the human eye was analyzed, and two asymmetric design methods were introduced: rotational translation offset and interpolation shift. Secondly, an offset function was set, and the interpolation function through the initial offset point was constructed by using Lagrange interpolation, Newton interpolation, and cubic spline interpolation. Thirdly, by setting two boundary conditions of two sets of offset point values and cubic spline interpolation values on two sets of meridians, three interpolation algorithms were analyzed and compared. Finally, the optical power and astigmatism distribution were given through simulation and actual processing. The experimental results show that the cubic spline interpolation in the interpolation algorithm is smoother and has no inflection point, the astigmatism gradient of the two asymmetric design methods in the near and far areas has achieved a smooth transition, the maximum astigmatism is reduced from 1.125 times the added luminosity to 0.875 times the added luminosity, and the offset angle is between 20° and 23°, which basically meets the characteristics of automatic convergence of the human eye and improves the problems of distortion and distortion of human vision.
摘要:In order to simultaneously measure the 3D shape and relative position between two working surfaces of the double-specular-surface objects, we established a common benchmark metrology measurement system based on direct phase measuring deflectometry. To complete system calibration and common benchmark calibration, we designed and fabricated a double-specular-surface calibration plate. First, we calibrated the two subsystems forming the common benchmark morphology measurement system in depth and lateral direction. This established the relationship between absolute phase and depth, pixel coordinates and spatial coordinates X, Y. Next, to avoid the problem of low calibration accuracy caused by the manufacturing error of the double-specular-surface calibration plate, we performed common benchmark calibration to take advantage of the spatial constraint relationship. This allowed us to convert 3D point clouds located in different coordinate systems to a unified coordinate system. Finally, we conducted practical experiments on specular-surface steps and a high-precision measuring block using the common benchmark metrology measurement system. Based on the experimental results, the following conclusions are drawn: the root mean square error of distance between the two surfaces of the measuring block is 0.076 mm, which shown that the proposed common benchmark calibration method is effective in obtaining the double-specular-surface metrology; the maximum absolute error in distance between two adjacent surfaces of the specular surface steps is 0.032 mm, which shown that the error caused by common benchmark calibration reduces the measurement accuracy of the common benchmark metrology measurement system. To improve the accuracy of the common benchmark metrology measurement system, subsequent studies will optimize the common benchmark calibration method.
摘要:To achieve measurement of drill pipe thread parameters in an automated and contactless method, this paper proposed a scanning measurement method for large taper thread profile by a short-range sensor based on the spectral confocal measurement principle. This method used the cooperative movement of the spectral confocal sensor and the measured thread to quickly obtain the cross-sectional profile data passing through the thread axis, which characterized the thread surface quality. To correct the measurement error caused by the non-coaxiality of the thread axis and the rotary table axis, a conical thread point laser measurement model was established, a thread tooth profile distortion compensation algorithm was developed, and a two-dimensional laser measurement system for the inner thread parameters of the drill pipe joint was developed and integrated with the automated production line. The measurement system adopted a vertical structure and was mainly composed of a base, a precision five-axis displacement platform, a grating sensor, a control system, a software system, etc. At the same time, a two-dimensional measurement and evaluation software for the inner thread parameters of the drill pipe joint was developed to calculate and evaluate key parameters such as pitch, tooth height, taper, tooth profile angle, and base diameter. Experimental results show that the compensation rate of the base diameter by the tooth profile distortion compensation algorithm is 45.4%, the compensation rate of the tooth profile half-angle is 45%, the compensation rate of the taper is 26.7%, the compensation rate of the tooth height is 25%, and it has almost no effect on the pitch; the measurement accuracy of the developed measurement system can reach ±2 μm, and the measurement cycle is 102 seconds. Compared with the traditional measurement method, this measurement system has the characteristics of non-contact measurement, high automation, and high precision, which meets the precision requirements of drill pipe thread measurement.
关键词:drill pipe thread;thread measurement;contour scanning measurement;spectral confocal sensor;parameter of thread
摘要:Through a series of simulation and experimental observation, the damage process of 1 μm high power continuous laser on 304 stainless steel was deeply analyzed, and the influence of different power density, material thickness and thermal coupling on the material burn-through time and its change rule were emphatically discussed. The results show that with the increase of stainless steel thickness, the influence of thermal stress and temperature gradient on material deformation and crack formation is intensified, resulting in the increase of laser power density and time required for penetration. The contribution of thermal stress further accelerates the failure process of the material, especially at higher power density, thermal deformation and stress concentration significantly affect the mechanical properties of the material. As a result, there are significant differences in the penetration damage threshold of 304 stainless steel with a thickness of 0.5-2 mm under high power continuous laser irradiation. Finally, the functional relationship between laser irradiation time and material thickness and breakdown threshold is obtained through numerical analysis and data fitting, so as to achieve quantitative evaluation of the penetration and damage characteristics of 304 stainless steel with high power continuous laser.
摘要:With the development of rehabilitation medical technology and improving the accuracy of upper limb rehabilitation effect, the research on efficient and accurate upper limb parallel rehabilitation institutions is becoming increasingly critical. In this paper, a new parallel rehabilitation mechanism for upper limbs was proposed and its kinematics and dynamics are analyzed. The 2UU-PSU Dof was investigated, the closed-loop vector method was used to solve the pose and derive the kinematics equation, and the rationality of the mechanism motion was verified. Based on the Lagrange method, dynamic equation was established for dynamic analysis. To verify the correctness of the kinematic derivation, the experimental platform of 2UU-PSU was built, and experiments were carried out based on NOKOV dynamic trapping equipment. Finally, the adaptive fuzzy PID control is established, and the 2UU-PSU mechanism is co-simulated by ADAMS and MATLAB Simulink. The experimental results show that: in the experiment of the 2UU-PSU mechanism based on the NOKOV dynamic trapping equipment, the max REMS of the pose measurement of the moving platform is 6.89%,1.81% and 9.73%, respectively. The max REMS of the three branched-chain dynamics between the simulation results and the theoretical data is 2.50%,2.40% and 2.96%, respectively. From the theoretical and simulation analysis and experimental verification results, the root mean square error of kinematics and dynamics of the 2UU-PSU mechanism is at a low level, indicating that the mechanism has rationality and reliability in terms of kinematics and dynamics, and can provide an effective basis for the design and research of related rehabilitation institutions. It also provides a valuable reference for other dynamic research on parallel rehabilitation institutions with less Dof .
关键词:2UU-PSU;parallel mechanism;reverse position solution;lagrange method;dynamics
摘要:Cryogenic space telescope is applied in 90K cryogenic environment, but developed in a laboratory environment at room temperature and pressure. The huge differences in application and development environments result in two different sets of parameters of optical components. A telescope with good image quality at cryogenic temperature is actually a system with large aberration in laboratory environment. In order to quantitatively evaluate the imaging quality of a cryogenic telescope, a structural thermos optical performance simulation was conducted,and a testing method for wavefront error of the telescope in a 90 K cryogenic environment was designed. Firstly, the working temperature of the telescope at 90 K is achieved through the dual cooling of liquid nitrogen cold shroud radiation and refrigeration machine in the vacuum chamber. The wavefront measurement of the telescope is achieved through the interference measurement of parallel light tube beam expansion. Secondly, the error sources of the testing system were analyzed and calibrated to correct the test results. Finally, the consistency between the measured cryogenic wavefront values and the model simulation of the telescope was compared and analyzed, as well as the manifestation of wavefront errors and the corresponding mapping relationship of structural design. The experimental results show that the design simulation of the telescope is accurate, the 90 K low-temperature wavefront testing method is reasonable and feasible, the simulation accuracy is better than 20 nm,and the wavefront testing accuracy is better than 9 nm. The test results can be used for the design improvement of the optical mechanical system of the space telescope.
关键词:telescope;design simulation;wavefront at cryogenic;interferometric measurement
摘要:The fused silica micro-hemisphere resonator gyroscope is one of the most promising miniature vibratory gyroscopes, offering advantages such as a simple structure, high precision, and strong anti-interference capability. The micro-hemisphere resonator is the core component of the gyroscope, and its fabrication process is critical for performance. This study proposed a method to improve release quality while maintaining processing efficiency. In this study, a femtosecond laser was used for the release process, with the laser focused on the lower surface of the fused silica resonator through a silicon reflective target placed beneath it. This setup enhanced the intensity of the femtosecond laser inside the material, improving both the release speed and surface quality. A simplified mathematical model for laser intensity distribution inside fused silica and FDTD simulations were employed to analyze the laser energy field during femtosecond laser processing. The optimal process parameters were determined from the analysis. Experimental results show that when the single pulse energy is set at 2.2 μJ and the release speed is between 0.2 mm/s and 0.5 mm/s, a 300 μm thick quartz sheet was released with a release width ranging from 34.31 μm to 35.16 μm, and a surface roughness less than 400 nm. The release width increased by approximately 236% compared to the conventional focusing on the upper surface. This method effectively improves the release quality of the micro-hemisphere resonator, providing a solid technical foundation for the fabrication of high-quality fused silica resonators.
摘要:Aimed at the issue that the edge details of the dehazing images were insufficiently clear, and the majority of the existing U-Net dehazing networks did not adequately exploit the information in the frequency domain and neglected the information exchange among different channels, resulting in a blurry structure, a dual-scale fusion network with frequency-domain feature distillation was proposed for the effective dehazing of single images. In the Coarse-scale feature extraction subnet, a large-scale convolution kernel was utilized to extract image texture information, and a residual attention mechanism was employed to enhance the features related to haze. In the Fine-scale high-frequency fusion subnet, a high-frequency feature distillation module was devised to refine the extracted structure and edge information and gradually restore clear images. Meanwhile, the cross-fusion strategy was adopted to fuse the features of different channels. The experimental results indicate that compared with the MSTN algorithm(Efficient and Accurate Multi-Scale Topological Network), the peak signal-to-noise ratio and structural similarity on the outdoor image dataset have been enhanced by 9.98% and 4.77% respectively. The experimental results on diverse datasets demonstrate that the proposed approach exhibits superior performance. This method can effectively enhance the dehazing effect, retain more structural information, and possess better color detail recovery capability.
摘要:To improve the accuracy and stability of camera pose estimation in complex scenarios, this paper independently designed the ResGraphLoc network. This network further enhanced the pose regression accuracy of the camera in scenarios with occlusion, illumination changes, and low texture by introducing the residual network and the graph attention mechanism. The network adopted ResNet101 as the feature encoder and enhanced the significant feature extraction ability through the improved residual block. The graph attention layer was utilized to fuse multi-level feature maps and realized feature information diffusion and aggregation through the multi-head self-attention mechanism. Finally, the position and angle features were extracted from the feature embedding through the nonlinear MLP layer to complete the end-to-end camera pose regression. On the large-scale outdoor dataset, the pose error of the ResGraphLoc model was superior to the existing algorithms. In the LOOP and FULL scenarios, the pose regression results are 7.18 m, 2.48° and 16.96 m, 3.16° respectively, with an improvement of more than 25% compared to the benchmark model. In the 4Seasons dataset's Neighborhood scenario, the outdoor localization error can be as low as 1.40 m and 0.76°.In the indoor dataset with missing and repetitive textures, the position and angle regression results can reach 0.08m and 3.25° respectively. The experimental results verify the high accuracy and stability of ResGraphLoc in complex environments and can effectively cope with occlusion, illumination changes, and low texture scenarios.
摘要:A multi-source image matching method named PCMM-Net was proposed to address the problem of unmatched keypoints resulting from the different imaging mechanisms of visible and infrared images. Firstly, a U-Net model with a policy gradient mechanism was introduced as the baseline model to extract keypoints from the images. This foundational model transformed pixel values into normalized probabilities, serving to filter out low-texture areas. This process enabled the network to focus on and learn keypoints that were both reliable and repeatable. Then, to address the radiance discrepancies between visible images and infrared images, a pseudo-twin network was employed to extract similar features from local image patches. Finally, a fusion layer was proposed to integrate similar features and features from keypoint detectors, generating descriptors suitable for multi-source image matching. The proposed algorithm was validated for matching performance on the VEDAI near-infrared dataset and the MTV thermal infrared dataset. Experimental results demonstrate that the proposed algorithm achieves average matching accuracies of 97.77% and 95.88% on the VEDAI and MTV datasets, respectively. Compared to the DALF algorithm, the average matching accuracies are improved by 2.26% and 14% on VEDAI and MTV datasets. Experimental results show that the algorithm has better matching effect and improves the accuracy of matching.
关键词:visible and infrared images;multi-source image matching;deep learning;Convolutional Neural Network(CNN)
摘要:Dimensionality reduction plays a pivotal role in data visualization and preprocessing. Principal Component Analysis (PCA), a common unsupervised dim-reduction method, encounters challenges in practical applications as it is highly sensitive to noise and outliers. To address this issue, robust PCA methods had been developed, aiming to minimize the reconstruction errors induced by outliers. However, these methods frequently overlooked the local structure of data, resulting in a loss of critical structural information. This compromised the accurate identification and removal of noise and outliers, impacting subsequent algorithm performance. In response, we proposed a novel algorithm named Robust Principal Component Analysis Based on Soft Mean Filtering (RPCA-SMF). RPCA-SMF employed soft mean filtering and incorporated noise treatment in two stages: before and after model learning. Specifically, it used mean filtering to identify noise by comparing a sample's deviation from its local mean to that of its neighbors, applying soft weighting to samples. Subsequently, it leveraged the "discriminant knowledge" of noise from the first stage to process noise information. The mean filter preserved the overall silhouette information of the data. For samples identified as noise, RPCA-SMF emphasized the silhouette information at low frequencies rather than the high-frequency noise information. Thus, RPCA-SMF could effectively retain the useful data information. It also improved the ability to maintain the overall structural characteristics of the data. This made the algorithm robust and more generalizable.
关键词:dimensionality reduction;unsupervised feature extraction;principal component analysis;soft mean filtering;robust
摘要:Aiming at the autonomous decision-making problem of spacecraft approaching closely in the Earth-Moon environment, a decision-making method based on an improved Proximal Policy Optimization (PPO) algorithm was proposed to enable the tracking spacecraft to reach the state required for docking with the target spacecraft within a specified time. First, an LSTM network was introduced into the strategic network structure of the PPO algorithm to handle state inputs and increase the robustness of the algorithm in learning tasks with random parameters. Secondly, a state-based internal reward exploration mechanism was proposed to improve the algorithm's exploration ability by linearly superimposing it with the algorithm's basic reward. In addition, an importance sampling ratio constraint was designed and introduced into the strategy loss function to prevent high variance objective estimation from endangering the optimization of the objective function. Finally, the effectiveness of the proposed method was verified by comparing the learning reward and task execution results with other learning algorithms. The simulation results show that the learning reward value of the improved PPO algorithm is increased by 15%, the fuel consumption of performing close tasks is reduced by 57%, and the mission success rate is increased by 1% when there is unmodelled interference. This method can significantly improve the spacecraft's autonomous decision-making capabilities when performing close missions.
摘要:To address the issue of low pose estimation accuracy or complete failure of visual simultaneous localization and mapping (SLAM) algorithms that relied solely on single-point features in indoor environments characterized by sparse texture and varying illumination conditions, a pose-decoupled RGBD-SLAM system based on point, line, and plane features was proposed. This system leveraged the complementary advantages of different features and the structured characteristics of the scene, employing the concept of pose decoupled estimation. By utilizing the Manhattan World hypothesis, drift-free rotation estimation was achieved, while translation was estimated through the minimization of a multi-feature joint error function. This approach mitigated the cumulative error effects associated with traditional SLAM systems that employed frame-by-frame tracking, thereby enhancing the accuracy of pose estimation and facilitating the construction of a richly informative point-line-plane structural map of the environment. Experimental results indicate that the proposed SLAM system achieves an average absolute trajectory accuracy improvement of 54.5%, 23.5%, and 28.3% compared to ORB-SLAM2, PL-SLAM, and SP-SLAM, respectively, across eight subsequences of the ICL-NUIM dataset. Additionally, in eleven subsequences of the TUM RGBD dataset, improvements of 33.9%, 26.2%, and 11.7% are observed, demonstrating superior global localization performance and enhanced system robustness. Furthermore, the constructed point-line-plane structural map provides a more comprehensive representation of the environment.