Ensemble deep transfer learning driven by multisensor signals for the fault diagnosis of bevel-gear cross-operation conditions

The existing intelligent fault diagnosis techniques of bevel gear focus on single-sensor signal analysis under the steady operation condition. In this study, a new method is proposed based on ensemble deep transfer learning and multisensor signals to enhance the fault diagnosis adaptability and reliability of bevel gear under various operation conditions. First, a novel stacked autoencoder(NSAE) is constructed using a denoising autoencoder, batch normalization, and the Swish activation function. Second, a series of source-domain NSAEs with multisensor vibration signals is pretrained. Third, the good model parameters provided by the source-domain NSAEs are transferred to initialize the corresponding target-domain NSAEs. Finally, a modified voting fusion strategy is designed to obtain a comprehensive result. The multisensor signals collected under the different operation conditions of bevel gear are used to verify the proposed method. The comparison results show that the proposed method can diagnose different faults in an accurate and stable manner using only one target-domain sample, thereby outperforming the existing methods.     

建筑物三维景观模型的质量检查及评价方法探讨

针对目前三维模型质量控制规范的滞后,本文介绍了建筑物三维景观模型的主要检查内容和检查方法,然后在现有规范的基础上,根据工程应用的实际情况,采用缺陷扣分法,制订了一套初步的缺陷分类标准,并应用于我国南方某城市的建筑物三维景观模型的检查工作。     

T-shaped trifunctional crosslinker-toughening hydrogels

Currently, development of a single network hydrogel with a high fracture toughness in swelling equilibrium remains challenging.In this work, a novel T-shaped trifunctional crosslinker(T-NAGAX) with dual vinyl on the backbone and dual amide group on the side chain is synthesized by Michael addition and acylation. The T-NAGAX is used to prepare chemically crosslinked hydrogel by one-pot photo-initiated polymerization. The resulting single network hydrogels of representative polyacrylamide(PAAm), poly(N-acryloyl 2-glycine)(PACG), and poly(N-isopropyl acrylamide)(PNIPAM) crosslinked with T-NAGAX with additional hydrogen-bonds exhibit much better fracture toughness than that of the corresponding hydrogels crosslinked by N,N'-methylene bisacrylamide, a conventional crosslinker; higher mechanical strengths are observed in the T-NAGAX crosslinked hydrogels. These hydrogels are promising to be exploited as load-bearing soft tissue substitutes. This T-NAGAX crosslinker can be expanded to toughen various types of hydrogels.     

A robust visual SLAM system in dynamic man-made environments

This paper presents a robust visual simultaneous localization and mapping(SLAM) system that leverages point and structural line features in dynamic man-made environments. Manhanttan world assumption is considered and the structural line features in such man-made environments provide rich geometric constraint, e.g., parallelism. Such a geometric constraint can be therefore used to rectify 3 D maplines after initialization. To cope with dynamic scenarios, the proposed system are divided into four main threads including 2 D dynamic object tracking, visual odometry, local mapping and loop closing. The 2 D tracker is responsible to track the object and capture the moving object in bounding boxes. In such a case, the dynamic background can be excluded and the outlier point and line features can be effectively removed. To parameterize 3 D lines, we use Pl ¨ucker line coordinates in initialization and projection processes, and utilize the orthonormal representation in unconstrained graph optimization process. The proposed system has been evaluated in both benchmark datasets and real-world scenarios, which reveals a more robust performance in most of the experiments compared with the existing state-of-the-art methods.     

Primary exploration of nonlinear information fusion control theory

By introducing information fusion techniques into a control field, a new theory of information fusion control (IFC) is proposed. Based on the theory of information fusion estimation, optimal control of nonlinear discrete control system is investigated. All information on control strategy, including ideal control strategy, expected object trajectory and dynamics of system, are regarded as measuring information of control strategy. Therefore, the problem of optimal control is transferred into the one of information fusion estimation. Firstly, the nonlinear information fusion estimation theorems are described. Secondly, an algorithm of nonlinear IFC theory is detailedly deduced. Finally, the simulation results of manipulator shift control are given, which show the feasibility and effectiveness of the presented algorithm.     

Adaptive preview control with deck motion compensation for autonomous carrier landing of an aircraft

In this article, an autonomous carrier landing problem of an aircraft is addressed by developing an autonomous carrier landing system (ACLS) composed of previewable guidance and control systems. In the guidance system, an appropriate touchdown point is estimated by predicting the seakeeping motion of the deck by unscented Kalman filtering technique, which is then utilized to adjust the reference glide path and produce an effective deck motion compensation, indispensable for a safe landing. The adaptive preview control (APC) scheme is proposed, which utilizes future reference information. The feedback and feedforward adaptive gains are derived through the Lyapunov stability theorem ensuring better tracking response and disturbance rejection. Hence, the asymptotic stability of the closed-loop system is guaranteed. The simulation results depict better performance of the proposed ACLS in the presence of deck fluctuations and airwake disturbance compared with PID and LMI based preview control schemes.     

Coherence-enhancing line drawing for color images

Line drawing plays an important role in many image-based non-photorealistic applications. However, most existing approaches use a grayscale edge detector for line extraction, so that only luminance differences between nearby image pixels is taken into account, but the chrominance differences is ignored. This leads to the undesirable consequence that visually significant edges in adjacent regions with different colors of similar luminance cannot be detected. To address this limitation, we present a novel enhanced line drawing method based on a flow-based difference-of-Gaussians （FDoG） filter. Because of an inherent property of the thresholded DoG edge model, captured lines may appear dislodged from the true edges in the image. To this end, we provide a gradient-guided warping technique so that smooth and coherent lines can be extracted in the correct location. The GPU implementation of the proposed algorithms allows real-time performance, and experimental examples with various color images demonstrate the method＇s superior qualitative performance over previous approaches.