The offshore platform tower crane is affected by sea breeze, which causes severe vibration, which causes damage to the crane structure and reduces the working efficiency and performance of the crane. Therefore, the vibration suppression under the complex environment of sea breeze has become a key problem to be solved in practical engineering. Firstly, a pulsating wind excitation model with wind speed changing at any time is established to simulate the time sequence of downwind and crosswise wind loads, which is used to reflect the actual wind speed fluctuations. Secondly, the pulsating wind model is applied to the crane finite element model, and the structural vibration characteristics are explored by analyzing the dynamics of the tower crane under wind excitation，the dynamic model of tower crane system under pulsating wind excitation is established, and the system state equation is constructed. Considering the vibration displacement performance of tower crane structure, a hybrid [Formula: see text] optimal performance vibration active control strategy is proposed. Finally, simulation experiments are carried out. The results show that, compared with the AA controller under the same conditions, the root mean square of displacement under downwind excitation decreases by 65.77%, 64.31% and 63.13%, respectively, and the root mean square of displacement under transverse wind excitation decreases by 62.8%, 65.51% and 62.6%, respectively. The results show that the proposed control method can effectively suppress tower crane vibration.

Extracting knowledge and constructing domain knowledge graphs from used vehicle maintenance records can reveal the mechanism of faults. However, maintenance records are semi-structured documents containing both structured and unstructured data. Here, we propose a topic joint model to improve the accuracy of knowledge extraction from used vehicle maintenance records. First, we apply the weighted latent Dirichlet allocation method to extract the hidden topic distribution of fault cases. Then, a bidirectional encoder representations from transformers (BERT) -based method is developed to identify the position and category information of fault entities with case-topic features. Finally, we used real data of vehicle maintenance records to verify the efficacy of our proposed method. The results show that when using real-world data, the proposed joint model has a higher accuracy than the standard knowledge extraction method, which is achieved by combining topic features for entity recognition and relationship extraction tasks. The F1 scores of entity recognition and relationship classification were 75.46 and 78.42, respectively.

In industrial systems, textual failure records note the failure mechanisms, the parts involved, and the failure symptoms; these records guide fault analysis and repair. However, case retrieval and feature extraction require extensive prior knowledge and diagnostic expertise; this method is time-consuming and labor-intensive. In this article, we present a novel two-stage framework that automatically extracts and generates features from very large textual records. We use an improved weighted latent Dirichlet allocation model and the Word2vec method to extract topic category and semantic features from fault texts; this approach accelerates training convergence. Next, we build a topic-context attention model in which word-embedding semantic features interact with topic features. Finally, we use classification and similarity calculation models to diagnose faults and retrieve similar cases; this approach ensures feature generation. Our method is very granular in terms of case representation which significantly improves diagnosis. The method robustly identifies similar cases by interrogating vehicle maintenance records.

A comprehensive review of the research progress in the structural integrity of solid rocket motor grain is presented, including mechanical properties of propellant and bonding interfaces, failure mechanisms, motor grain and propellant numerical simulation methods, and motor grain testing technology. The current trends or challenges in the studies about the structural integrity of solid rocket motor grain are also proposed. It is pointed out that in the future, the research direction and emphasis should be placed mainly on developing multi-scale characterizations and testing methods of propellants and bonding interfaces, advanced numerical simulation methods, comprehensive testing techniques for grains and eventually constructing an integrated evaluation platform.

Assembly instructions are critical for prompt fulfilment of assembly tasks. However, the design of such instructions is time-consuming and requires experience. Retrieve and reuse of previous cases shortens the design time and reduces design mistakes, whereas the traditional retrieval method encounters a bottleneck during encoding because the technical instructions include both structured and unstructured data. In this paper, we propose a hierarchical retrieval approach for automatic generation of assembly instructions based on previously used technical instruction cards. First, a case-based reasoning (CBR) method is employed to encode the assembly process and retrieve the suitable cases. Then, an improved weighted latent Dirichlet allocation text mining technique is applied to explore unstructured text topics and recommend the most optimal case. Finally, we utilize the proposed method to an automotive assembly process using data in 12,034 used instruction cards. The results demonstrate that technical instructions can be generated automatically for a specific topic using the proposed retrieval method. Compared to the traditional CBR method, the proposed hierarchical retrieval approach significantly improves the quality of new assembly instructions and the speed of generation.

Accurate makespan estimation is imperative during production scheduling to increase the flexibility and efficiency of work plans. However, given the complexities of production systems and product customizations, it is challenging to estimate makespans with high accuracy. In this paper, we propose a topic model-based neural network (TM-NN) method to increase the accuracy of makespan estimation for assembly processes. First, unlike traditional methods that use influential factors as inputs, we extract assembly features using a latent Dirichlet allocation model that mines latent topic information from an assembly instruction corpus. Then, the assembly process is represented as a sequence model with both assembly topics and features of the product physical characteristics, the assembly process, the equipment, the personnel, and uncertainty. Finally, we use a structured numerical vector as the input to machine learning-based predictive models, including a neural network, a random forest, and a support vector machine, and estimate makespans. The results show that the proposed TM-NN method effectively extracts latent topics in assembly documents and significantly increases the accuracy of makespan estimation.

To address the problem such as complex operation and poor usability in the traditional fringe projection measurement method, a flexible fringe projection measurement model based on phase height mapping was proposed. The mapping relationship from absolute phase value to the spatial coordinates was built by the measurement model, without considering the geometric constraints between the camera and the projector. The proposed calibration method needed neither the geometric constraint relationship between the camera and the projector, nor high-precision auxiliary tools such as gauge block or high-precision displacement stage. It only needed a checkerboard calibration board to complete the system calibration. The measurement system had the advantages of simple structure, high efficiency, high accuracy and good usability. Simulation and experiments had been performed to validate the effectiveness of the measurement model.

In response to the traditional MPC algorithm's difficult parameter adjustment leading to the inability to steer in a timely and accurate manner to avoid collisions, this paper designs an optimisation algorithm based on the simulated annealing algorithm with automatic parameter adjustment MPC. A vehicle dynamics model and a prediction model are established, and the simulated annealing algorithm is used to solve the objective function of the predetermined trajectory and obtain the weight matrix applicable to the prediction model. MPC the optimised controller is used to achieve the steering and collision avoidance trajectory tracking control of the vehicle. The simulation results under two operating conditions of medium and high-speed show that the controller can achieve fast response of vehicle steering and collision avoidance at different speeds and can keep the tracking error within 5%. The controller has the characteristics of timeliness, accuracy and stability.

激光测速雷达较传统大气数据系统在测量精度方面有显著的优势.为了能够在稳定流场下实现对比测试,将激光测速雷达和高精度超声波风速风向仪一同放置于风塔200 m高度进行长时间对比.以10 min、1 min、1 s、0.1 s为尺度对两者测量的真空速(风速)和侧滑角(风向)进行分析.数据表明激光测速雷达的测量精度和超声波风速风向仪(速度精度0.18 m/s、风向2°)是同级别的.

为了解决齿轮啮合状态检测需要大量数据样本的难题,提出了一种基于相位测振技术的齿轮啮合状态检测方法.通过使用相机拍摄齿轮箱,从所拍视频中提取多个位置的振动信号,对振动信号建立时频域特征值,最后使用随机森林分类来完成检测.以某开式齿轮箱为对象,通过试验证明了所提方法的准确性和有效性.

反垄断法的域外适用最早正式确立于美国,随后完善于欧盟和德国等国家,起初我国并没有关于反垄断法的域外适用条款,但是随着经济全球化的浪潮,以及我国"走出去"的发展等原因使得我国与世界经济的交流日益频繁.在这样的时代背景下我国由最初的被迫卷入到现在的主动加入,都不得不重视运用有"小宪法"之称的反垄断法的域外条款来保护国内市场经济的有序竞争.有基于此,我国2008年颁布的《反垄断法》便在第二条规定了反垄断法的域外适用条款可谓具有进步意义,但是该规定的不完善之处却在实践中引发了一系列问题.

军事技术产能过剩、市场经济缺乏活力、以民促军趋势显现都是我国国防专利转化的推动力量.然而现实情况中,国防专利转化却面临着可以转化,但涉及商业秘密;选择转化,但解密遥遥无期;已经解密,但缺乏共享平台三重困境.为此,本文在分析困境成因的基础上,寻找出国防专利转化的三条出路.第一条为明确产权归属、合理分配收益的积极鼓励转化之路;第二条为利用脱密代替解密、建立强制解密制度的科学推动解密之路;第三条为搭建共享平台、筛选发布内容、规范内容形式、健全体制机制的完善共享平台之路.

Traditional renal puncture surgery requires manual operation, which has a poor puncture effect, low surgical success rate, and high incidence of postoperative complications. Robot-assisted puncture surgery can effectively improve the accuracy of punctures, improve the success rate of surgery, and reduce the occurrence of postoperative complications. This paper provides a dual-armed robotic puncture scheme to assist surgeons. The system is divided into an ultrasound scanning arm and a puncture arm. Both robotic arms with a compliant positioning function and master–slave control function are designed, respectively, and the control system is achieved. The puncture arm’s position and posture are decoupled by the wrist RCM mechanism and the arm decoupling mechanism. According to the independent joint control principle, the compliant positioning function is realized based on the single-joint human–computer interactive admittance control. The simulation and tests verify its functions and performance. The differential motion incremental master–slave mapping strategy is used to realize the master–slave control function. The error feedback link is introduced to solve the cumulative error problem in the master–slave control. The dual-armed robotic puncture system prototype is established and animal tests verify the effectiveness.

螺纹连接松动被认为是导致管接头密封性能衰退的因素之一,但工程中缺少证明该观点的试验数据.本文基于HB 6442-90规定的旋转弯曲疲劳试验方法,以74°锥面管接头为研究对象,验证了往复载荷作用下管接头的螺纹连接可能出现松动并导致管接头密封性能逐渐衰退.本文还对传统的管接头进行了改进,引入了一种新型防松螺纹,通过试验验证了该防松螺纹可以有效避免管接头的螺纹松动,从而显著提升管接头密封性能的稳定性.

为解决工程中齿轮轴系装配误差的测量难题,提出了一种基于立体视觉的齿轮轴系装配误差测量方法.该方法以布置在待测特征上的圆形标记点为媒介,通过三维重建与数学拟合,获取相应特征的空间位姿,进而计算装配误差.以某锥齿轮箱为对象,给出了所提方法的完整技术流程,并系统研究了状态数量和靶标盘安装角度对拟合精度的影响.开发了完整的软硬件系统,通过实验,验证了测量方法的有效性与高效性.

The fringe projection profilometry (FPP) technique has been widely applied in three-dimensional (3D) reconstruction in industry for its high speed and high accuracy. Recently, deep learning has been successfully applied in FPP to achieve high-accuracy and robust 3D reconstructions in an efficient way. However, the network training needs to generate and label numerous ground truth 3D data, which can be time-consuming and labor-intensive. In this paper, we propose to design an unsupervised convolutional neural network (CNN) model based on dual-frequency fringe images to fix the problem. The fringe reprojection model is created to transform the output height map to the corresponding fringe image to realize the unsupervised training of the CNN. Our network takes two fringe images with different frequencies and outputs the corresponding height map. Unlike most of the previous works, our proposed network avoids numerous data annotations and can be trained without ground truth 3D data for unsupervised learning. Experimental results verify that our proposed unsupervised model (1) can get competitive-accuracy reconstruction results compared with previous supervised methods, (2) has excellent anti-noise and generalization performance and (3) saves time for dataset generation and labeling (3.2 hours, one-sixth of the supervised method) and computer space for dataset storage (1.27 GB, one-tenth of the supervised method).

Model-Based Systems Design (MBSD) formalizes the application of system modeling. However, it is still difficult for designers to implement MBSD in practice. One of the challenges is to make the field of design more unified, as different MBSD methodologies focus on specific areas, and various designers from different areas use ambiguous terms. Moreover, the failure of some products originates in undiscovered couplings of functions in the design stage. Axiomatic Design (AD) provides a scientific foundation for system design. In order to reduce ambiguity and alleviate functional couplings, this paper integrates AD with the MBSD and proposes a unified systems design approach, called Axiomatic Model-Based Systems Design (A-MBSD). A-MBSD uses four pillars: (a) the fundamental framework of AD; (b) the Independence Axiom; (c) a new behavior domain (BD); and (d) an A-MBSD modeling profile. Finally, the design of a Forest Fire Satellite Monitoring and Control System demonstrates that the proposed approach can improve unity and alleviate the coupling of functions in a system design.

To overcome the limitations of conventional manual percutaneous needle insertion procedure, this paper proposes a percutaneous needle insertion robotic system with functions of biopsy and ablation. First, the robotic system, which integrates a 4-DOF positioning robotic arm and a 2-DOF RCM wrist, is designed. The 4-DOF positioning robotic arm can realize the exact position of the puncture needle and the 2-DOF RCM wrist can accurately adjust the orientation the needle. The combination of these two modules can ensure the kinematic decoupling of the position and posture of the robotic system. Second, the kinematics model of the robotic system based on classical D-H method is established, and the forward kinematics and inverse kinematics of the robotic system are analyzed. Finally, the manufacturing and assembly of the overall robotic system is performed and the robotic arm can successfully achieve percutaneous biopsy and ablation for tumor in urinary system.

目前针对气体泄漏热成像检测系统性能的相关评价技术还不够成熟,相应评价指标的测试系统及其测量方法尚无系统的研究报道.而常规热成像系统的性能评价方法难以直接用于评价气体泄漏热成像检测系统对泄漏气体的探测能力,本文结合泄漏气体特性及各测试系统的特点,设计了一种可测量多类性能指标的气体泄漏热成像检测系统性能的测试评价系统,并以乙烯和甲烷气体为检测目标在实验室环境中分别对NECL、MRGC和MDGC三种评价指标进行了实验测量,结果表明了测试评价系统的可行性和实用性.