摘要:To achieve high-power blue semiconductor laser outputs, the packaging technology of blue light bars was studied herein. First, high-power gallium nitride (GaN) blue semiconductor laser bars were encapsulated using gold-tin hard solder. A copper-tungsten transition heat sink was used as a buffer layer to suppress the residual stress between the copper heat sink and GaN laser chips. The chips were eutectic bonded onto the copper-tungsten transition heat sink using a high-precision SMT machine. Because the quality of the SMD directly affects the output characteristics of the device, the focus was on analyzing the impact of the bonding temperature and pressure of the SMD machine on the device. The experimental results reveal that, when the bonding temperature of the mounter is 320 °C, bonding pressure is 0.5 N, and bonding time is 40 s, the solder layer interface cavity is the smallest, thermal resistance is the lowest (0.565 °C/W), and threshold current is also the lowest (4.9 A). When the injection current is 30 A, the maximum output optical power is 32.21 W, and the maximum solar-cell efficiency reaches 23.3%. Therefore, after optimizing the bonding temperature, bonding pressure, and bonding time, the technical solution of using gold-tin hard solder to eutectic bond blue semiconductor laser chips onto copper-tungsten transition heat sinks is an effective way to achieve high-power operation of blue semiconductor laser bars.
摘要:Double-flexible-beam-coupling structures are widely used in the aerospace field, such as in solar-wing-extension structures and solar-cell arrays. However, non-contact vibration measurements and system control are some issues associated with double-flexible-coupled-beam systems. To address these, herein, a measurement and control experimental platform based on a point-laser-structured-light-vision system was constructed, and point-laser-visual-vibration-measurement research and vibration-control-algorithm design were conducted. The point-laser-vision system was calibrated, and the vibration signal of the flexible beam was extracted via image processing combined with a geometric method. The system-dynamics model was established, and the parameters of the state-space equation were identified using a wavelet transform and optimization method. A direct adaptive fuzzy cooperative (DAFC) controller was designed to actively control the vibration of the double-flexible-beam system, and the Gazelle optimization algorithm was used to optimize the controller parameters based on the identification model. Visual-vibration detection and control experiments were conducted under fixed and translational motions of the double-flexible-coupled-beam system. The experimental results revealed that the designed point-laser-vision sensor demonstrated an improved vibration-measurement accuracy, and the DAFC controller exhibited a better control effect than the proportional derivative controller, as the former could suppress the vibrations of the double-flexible-coupling beam more rapidly.
摘要:A multiparameter model-guided polarization optimization method is proposed for polarization effect correction of a dual-coded snapshot spectropolarimeter. A full-link polarization effect model of the spectropolarimeter based on a digital micro-mirror device (DMD), prism-grating-prism (PGP), micro-polarizer array (MPA) detector, and multi-film system is established. Bidirectional attenuation of the spectropolarimeter with incident partially polarized light is analyzed. The relationship among wavelength, polarization degree of the incident light, and polarization effect is revealed. The polarization effect of the spectropolarimeter is optimized through targeted control of the refractive index and incidence angle, grating refractive index and constant, prism refractive index and top angle, and film refractive index and film thickness when the spectral line bending meets the reconstruction requirements. The simulation results show that the structural similarity (SSIM) of the optimized system is >0.8 and that the relative error of the system polarization effect is <4%. The polarization effect is reduced by at least 6% compared with that before optimization. When the polarization of the incident light is constant, the polarization effect of the system is inversely proportional to the wavelength. The experimental acquisition of spectral polarization reconstructed images of typical materials under a single exposure improves the relative error by at least 14.7% for metal and 63.6% for plastic. The necessity and feasibility of the proposed polarization optimization method are verified. This study lays a theoretical foundation for high-precision acquisition of multidimensional data in dual-coded spectropolarimeters.
摘要:To comply with the process of a space robot capturing a spacecraft and the subsequent auxiliary docking operation, precise control of the output force and position of the spacecraft docking device was studied herein. A spring damper buffer device was added between the joint motor and manipulator to prevent the joint from being damaged under the huge impact force generated during contact and impact. First, by combining Newton's third law, velocity constraints of the capture points, and closed-chain system geometric constraints, a dynamic model of the hybrid system after capture was obtained, and the impact effect and force were estimated based on momentum conservation. Then, the impedance model during docking was established through the kinematics of the spacecraft docking device relative to the base coordinate system. Subsequently, a robust adaptive-double-layer sliding-mode control strategy was developed. Combined with impedance control, this strategy employed a force load servo control system to accurately control the position and output force of the docking device to reduce the impact force during contact and impact. The control strategy featured a double-layer sliding-mode structure, with the first layer ensuring convergence of the hybrid system in finite time and the second layer being used to solve the high-gain problem of the controller. Finally, the stability of the system was proved using the Lyapunov theorem, and the effectiveness of the proposed strategy was verified through a numerical simulation. The simulation results indicate that the buffer device can reduce the impact force by 46.78% of the maximum at the given velocities. Moreover, the control accuracy of the output force is better than 0.5 N, while the accuracies of the position and attitude are better than 10-3 m and 0.5°, respectively.
关键词:dual-arm space robot;buffer device;auxiliary docking operation;impedance control;double layer sliding mode
摘要:The low-temperature, high-bonding direct writing of three-dimensional conductive structures poses a challenge to the manufacturing of flexible electronic composite devices. Based on the silver-ammonia complexation mechanism, a particle-free direct writing solution suitable for forming three-dimensional conductive structures has been developed in this study. The problem of metal particle aggregation was overcome, achieving long-term stability. Under low-temperature sintering conditions at 50 °C, the conductive fibers prepared using the silver-ammonia complex solution exhibit excellent conductivity, with resistance as low as 365 Ω/mm, surpassing those made with silver nanoparticle solutions. The fiber structures produced using the silver-ammonia complex solution have strong adhesion to flexible substrates and possess good self-stacking characteristics. By adjusting the number of fiber stacking layers from 10 to 50, the resistance of the conductive fibers can be controlled within the 6.7-34.1 Ω/mm range. A humidity sensor designed based on the silver-ammonia complex solution was tested in different saturated salt solutions to establish humidity environments. The sensor demonstrated excellent humidity responsiveness, with hysteresis as low as 3.2%, and exhibited ideal real-time response even under high humidity conditions. The particle-free direct writing solution holds promising prospects in the fabrication of flexible electronic products and finds wide applications in fields such as motion detection and health management.
关键词:electrohydrodynamic direct writing;silver ammonia complexation;low temperature sintering;humidity sensor
摘要:Kinematic calibration is a common method for enhancing the accuracy of articulated arm coordinate measuring machines (AACMMs). However, the residual errors after calibration can affect its measurement accuracy and stability. In this study, we propose a residual error compensation method based on a compound calibration and extreme learning machine to improve the measurement accuracy of AACMMs. First, we establish the kinematic parameter identification model based on the kinematic modeling of AACMM. Furthermore, we conduct angle parameter identification, length parameter identification, and length parameter scaling to complete the compound kinematic calibration. Subsequently, we construct the measurement configuration with the measurement angle, elevation angle, distance, and rotation angle as variables to analyze the residual error map. The proposed residual error compensation method is based on an extreme learning machine owing to the strong nonlinear relationship between the measurement configuration variables and the residual errors. We verify the validity of the proposed method through experiments. The results show that the maximum value of the single point measurement error of the AACMM decreases from 0.061 mm to 0.044 mm, the mean value of measurement error decreases from 0.023 mm to 0.017 mm, and the standard deviation of measurement error decreases from 0.011 mm to 0.007 mm after residual correction. Furthermore, the maximum length measurement error decreases from 0.137 mm to 0.074 mm, the mean measurement error decreases from 0.033 mm to 0.021 mm, and the standard deviation of measurement error decreases from 0.037 mm to 0.019 mm.
关键词:Articulated Arm Coordinate Measuring Machines(AACMM);residual;measuring configuration;extreme learning machine;compound calibration
摘要:This study designs a deployment mechanism based on the Bennett mechanism to address the synchronization and reliability issues of solid surface deployment antennas (SSDAs) caused by independent rotation around two axes. First, a position determination algorithm for the antenna petal based on a particle swarm optimization algorithm is proposed. Combined with the axis-angle theorem, the parameters of uniaxial deployment are obtained, and the deployment mechanism based on the Bennett mechanism is designed. Furthermore, the design scheme of the petal frame is proposed with topology optimization methods based on the motion trajectories of adjacent petals. The analysis results show that the design frame can reduce the reflector deformation by 62.5% and enhance the fundamental frequency by four times, which fully proves the effectiveness of the frame design. Using a 10 m aperture SSDA as an example, the deployment mechanism is established, whereas the kinematic and dynamic parameters during the deployment process are analyzed. The deployment mechanism is further derived into a non-overconstrained mechanism by introducing negative kinematic pairs. The results show that the deployment process of SSDA is stable and reliable; the package ratio reaches 0.384. The research methods and conclusions in this study provide technical references for the design of SSDA.
摘要:A light-weight and wide-bandwidth vibration exciter operating in dynamic overload environments was developed to conduct combined simulations of dynamic overload and time-varying vibration. A piezoelectric-hydraulic series hybrid vibration excitation method and corresponding configuration are proposed to solve the problem of narrow bandwidth with light weight or heavy weight with wide bandwidth. A six-element piezoelectric parallel excitation module was designed and the corresponding precise assembly technology was built, achieving a parallel excitation efficiency of 74.2%. A hydraulic embedded centering method is also proposed for the hydraulic actuator to operate in dynamic overload environments. In addition, a hydraulic excitation module with a novel cylinder-in-cylinder configuration was developed. The frequency-division control method for series hybrid excitation systems was designed based on a frequency divider, with the hydraulic and piezoelectric vibration excitation modules working coordinately and loading with equilibrium. Combining force balance control with zero-displacement feedback compensation, a centering control method was designed for the hydraulic excitation module. Thus, precise centering in dynamic overloads was accomplished. Two time-varying vibration control methods, namely variable gain and long-duration waveform replication methods, are proposed, and the integrative control system was developed as well. Performance tests show that the developed hydraulic-piezoelectric series hybrid vibration exciter features excitation abilities of acceleration over 6 grms and frequency band covering 10-2 000 Hz for a payload over 50 kg in centrifugal overload exceeding 60 g and overload rate exceeding 15 g/s, respectively. The exciter was installed on a dynamic centrifuge and applied in a number of tests for inertial sensors, assemblies, and systems with good load control effects. In comparison to real flight tests, the dynamic overload-vibration simulation technique presented in this paper provides a more efficient and more economical laboratory approach for testing functional properties of guidance and control systems of aircrafts and spacecrafts, especially for large sample test data accumulation.
摘要:Airborne laser data (Light Detection and Ranging, LiDAR) presents challenges in distinguishing between ground and grassland, and visible light vegetation indices are inadequate for differentiating between shrub and tree layers. Therefore, this study proposes the construction of a multi-band information image that integrates LiDAR point cloud data and RGB vegetation indices. The approach integrates multi-band information from LiDAR point cloud data and vegetation indices to create an enhanced image. The fine-grained canopy height model (CHM) is generated using laser point cloud data. Simultaneously, a high-resolution digital orthophoto image is created using unmanned aerial vehicle imagery data. Among the evaluated vegetation indices, the Differential Enhanced Vegetation Index (DEVI) was the most suitable and was fused with the CHM. Subsequently, the CHM+DEVI fused images were reconstructed to eliminate erroneous values. Training samples were constructed, and the classification regression tree algorithm was employed to segment the ground range and adaptively extract vegetation, such as trees, shrubs, and grasslands. Within the tree areas, the local maximum algorithm was applied to detect tree vertices, which served as foreground markers; meanwhile, the non-tree regions were assigned as background markers. The segmentation results were obtained using watershed transformation, and the accuracy of the extracted vegetation information was analyzed by comparing it with ground-truth data. The evaluation results demonstrate the superior performance of the proposed improved algorithm, with the overall recall rate, precision rate, and accuracy F1 score increasing by 3.2%, 3.9%, and 3.5%, respectively. Moreover, the accuracy of tree height measurements exhibited improvements of 1.7%, 6.4%, 1.8%, and 0.3% in the four quadrats. The effectiveness of the improved method was verified, and the higher the degree of vegetation mixing in the region, the better the extraction effect of the improved algorithm.
摘要:An adaptive feature-matching network is proposed to solve the common problem of object occlusion in object tracking. By calculating the pixel-level similarity between the query and memory frames, the network encodes the similarity relationship between an object and its background and obtains a pixel-level similarity matrix. By separating the query and memory frames, the network calculates the multi-dimensional similarity to focus on more areas in the query frame and adaptively weighs the memory frame through the calculated similarity matrix to improve the accuracy and robustness of object tracking. Additionally, the feature memory network selects and saves the memory frames, provides additional apparent information for feature matching, and allows the network to implicitly learn the moving trend of an object to achieve better tracking results. Experimental results show that this method performs well on GOT-10k, LaSOT, and other datasets. On GOT-10k datasets, compared with the STMTrack algorithm, the value of the proposed algorithm is improved by 1.8%. The visualization results show that the proposed algorithm is more robust in meeting the challenges of object occlusion and disappearance.
摘要:Defect detection in thin film transistor-liquid crystal display (TFT-LCD) circuits is a challenging task because of the complex background setting, different types of defects involved, and real-time detection requirements from industry. Traditional methods have difficulties in satisfying the dual requirements of detection speed and accuracy. To address this challenge, in this study, a deep learning method is developed for image classification based on the Swin Transformer technique. First, token merging is used to reduce the computational complexity of each layer of the model, thus improving computation efficiency. Then, a depthwise separable convolution module is introduced to add convolutional bias to reduce the reliance on massive data. Finally, a knowledge distillation method is applied to overcome the problem of reduced detection accuracy caused by the less-intensive computation design. Experimental results on the self-made dataset demonstrate that the proposed method achieves a 2.6 G FLOPs reduction and a 17% speed improvement compared to baseline models, with only a 1.3% Top-1 accuracy precision reduction. More importantly, the proposed model achieves better balance on accuracy and detection speed on both self-made and public datasets than existing mainstream models on image classification in the TFT-LCD manufacturing industry.
关键词:Thin Film Transistor Liquid Crystal Display(TFT-LCD);transformer;image classification;computer vision
摘要:To address the problem of low accuracy of building extraction in high-resolution remote sensing images due to the diverse shapes and sizes of buildings and large number of parameters in traditional segmentation models, a Lightweight Multi-scale Difference network (LMD-Net) based on encoding-decoding is proposed. First, to avoid the invalid parameters caused by the degraded model performance due to the stacking of single feature processing units, a lightweight differential model is designed to improve the performance by integrating the functional differences of codec structures. Next, a Multi-scale Dilation Perception (MSDP) module is introduced to enhance the ability of the network to capture multi-scale target features. Finally, the double fusion mechanism is used to effectively aggregate the feature information of the deep jump connection and deep decoder to enhance the feature recovery ability of the decoder. To verify the validity and applicability of LMD-Net, the open source WHU building dataset was used as the data source to evaluate the accuracy and efficiency of LMD-Net and the common semantic segmentation network as well as the results from recent relevant literature. The results show that LMD-Net has obvious advantages in both efficiency and accuracy, which not only greatly reduces the parameter number and calculation amount of the model but also improves the intersection ratio and accuracy by 3.23% and 2.57%, respectively. Consequently, this model is advantageous in the field of building extraction based on high-resolution remote sensing images to generate an urban spatial information base.
摘要:In order to realize the operation of components without cooperation markers in on-orbit services, it is necessary to segment the area of the relevant components finely and then track them stably. For the refinement segmentation of components, firstly, the instance segmentation network, Mask RCNN, is trained on the spacecraft component instance segmentation dataset, and secondly a mask refinement module is added to its mask segmentation branch to optimize the component segmentation results. As to component tracking, a hierarchical weighted quintuple loss based on the Quit_trihard loss is proposed to train a re-identification network on the component re-identification dataset, and then the re-identification network trained before is embedded into the Deep OC SORT tracking algorithm for stable component tracking. The experimental results show that after mask optimization, the component segmentation accuracy of the relevant instance segmentation algorithm on the component segmentation test set can be improved to 84.90 mAP; by using the improved loss, the identification success rate on the component re-identification test set is improved to 76.86%, and the tracking success rate of the correlation tracking algorithm on the component tracking test set is improved to 89.38%. Therefore, the method proposed in this paper can basically satisfy the fine segmentation and stable tracking of spacecraft components.