Measurement-driven Gauss-Hermite particle filter with soft spatiotemporal constraints for multi-optical theodolites target tracking

Multi-Optical Theodolite Tracking systems (MOTTs) can stealthily extract the target’s status information from bearings only through non-contact measurement. The constrained MOTTs are partially compatible, yet many existing research works and results are based on the known model, ignoring its discrimination with the target maneuvering behavior pattern. To compensate for these mismatches, this paper develops a Measurement-driven Gauss-Hermite Particle Filter (MGHPF), which elegantly fuses the spatiotemporal constraints and its soft form to perform MOTT missions. Specifically, the target dynamic model and tracking algorithm are based on the target behavior pattern with the adaptive turn rate, fully exploiting the spatial epipolar geometry characteristics for each intersection measurement by a minimax strategy. Then, the center of the feasible area is approximated via the analytic coordinate transformation, and the latent samples are updated via the deterministic Gauss-Hermite integral method with the target’s predictive turn rate. Simultaneously, the effects of truncation correction and compensation feedback from the current measurement and historical estimation data are adaptively incorporated into the PF’s importance distribution to cover the mixture likelihood. Besides, an effective causality-invariant updating rule is provided to estimate the parameters of these soft spatiotemporal constrained MOTTs with convergence guarantees. Simulated and measured results show good agreement; compared with the state-of-the-art Multi-Model Rao-Blackwell Particle Filter (MMRBPF), the proposed MGHPF improves the filtering accuracy by 7.4%-34.7% and significantly reduces the computational load.     

智能制造技术在航天大型构件中的应用

智能制造是制造技术、系统工程、人工智能与网络技术等学科互相渗透、互相交织而形成的一门综合技术，可为高品质复杂零件制造提供新的解决方案，特别适应航天多品种、小批量生产的需要。本文分析了航天大型构件的生产制造现状，并列举了智能制造在航天构件领域应用的情况，分别从体系构架、工艺技术、制造装备、生产管理方面阐述了智能制造的实践应用。结合企业近年来的工作，从数字化的航天产品工艺设计和管理、面向航天复杂构件的智能化装备升级、全过程透明化的智能运营管控、航天智能焊接车间建设探索、数字孪生技术实现虚实融合等几个方面展开论述。     

Comparison study of ductile iron produced with Martian regolith harvested iron from ionic liquids and Bosch byproduct carbon for in-situ resource utilization versus commercially available 65-45-12 ductile iron

As researchers continue to study methods to facilitate long-term missions beyond low-Earth orbit, the ability to manufacture high-quality mechanical and structural components on the Lunar and Martian surfaces remains a crucial piece to the puzzle for a sustained presence. Due to the immense cost of sending supplies to extraterrestrial bodies, in-situ resource utilization (ISRU) methods are critical for the success and feasibility of these habitation missions. Ionic liquids (ILs) are currently being studied at NASA’s Marshall Space Flight Center (MSFC) to harvest elemental metals from meteorites and regolith minerals. Additionally, the Bosch process is being explored as a life support system at MSFC for oxygen (O₂) regeneration, rendering a byproduct of elemental carbon (C). In this investigation, the viability of casting ductile iron (DI) using IL-sourced iron (IL-Fe) and Bosch C was studied given the range of applications and performance of DI as an as-cast alloy. Ingots were produced using commercial elements to simulate the use of IL-Fe with C sourced from the byproduct C of the Bosch process. Samples were cast and compared to commercially available 65–45-12 DI with phase transformation diagrams, microstructures, and hardness. Results showed that IL-sourced elements are a viable source of elemental alloying materials for a range of DI alloys, with some limitations.     

A new interpretable fault diagnosis method based on belief rule base and probability table

It is vital to establish an interpretable fault diagnosis model for critical equipment. Belief Rule Base (BRB) is an interpretable expert system gradually applied in fault diagnosis. However, the expert knowledge cannot be utilized to establish the initial BRB accurately if there are multiple referential grades in different fault features. In addition, the interpretability of BRB-based fault diagnosis is destroyed in the optimization process, which reflects in two aspects: deviation from the initial expert judgment and over-optimization of parameters. To solve these problems, a new interpretable fault diagnosis model based on BRB and probability table, called the BRB-P, is proposed in this paper. Compared with the traditional BRB, the BRB-P constructed by the probability table is more accurate. Then, the interpretability constraints, i.e., the credibility of expert knowledge, the penalty factor and the rule-activation factor, are inserted into the projection covariance matrix adaption evolution strategy to maintain the interpretability of BRB-P. A case study of the aerospace relay is conducted to verify the effectiveness of the proposed method.     

航天器制造领域数字孪生技术的探索与实践

从实现航天器单件、小批量生产质量、柔性、效率同步提升的需求出发，回顾了数字孪生技术的内涵和发展，提出了包含产品孪生-产线孪生的航天器制造系统数字孪生的基础模型和动态演化过程，提出了数字孪生在数据采集、同步建摸、系统评估和生产线重构等技术方面的实现方法，阐述了采用数字孪生的虚实互动机制提升的具体实现途径，并通过航天器产品生产的具体应用验证了有效性。     

Topology optimization of turbine disk considering maximum stress prediction and constraints

For the stress-constrained topology optimization of a turbine disk under centrifugal loads, the jagged boundaries of the mesh and the gray densities on the solid/void interfaces could make the calculated stress field inconsistent with the actual value. It may result in overestimating the maximum stress and thus affect the effectiveness of stress constraints. This paper proposes a new method for predicting the maximum stress to overcome the difficulty. In the process, a predicted density is newly defined to obtain stable boundaries with thin layers of gray elements, a transition factor is innovatively proposed to evaluate the effects of intermediate-density elements, two different stiffness penalty schemes are flexibly used to calculate the elastic modulus of elements, and a linear stress penalty is further adopted to relax the stress field of the structure. The proposed approach for predicting the maximum stress value is verified by the analysis of a structure with smooth boundaries and the topology optimization of a turbine disk. An updating scheme of the stress constraint in the topology optimization is also developed using the predicted maximum stress. Some key ingredients affecting the optimization results are discussed in detail. The results prove the effectiveness and efficacy of the proposed maximum stress prediction and developed stress constraint methods.     

Model predictive control for close-proximity maneuvering of spacecraft with adaptive convexification of collision avoidance constraints

This study investigated model predictive control (MPC) for close-proximity maneuvering of spacecraft. It is essential for a designed MPC to effectively handle collision avoidance between the servicer spacecraft and the client spacecraft, especially while the client is rotating. The rotating motion of the client leads to dynamic changes in the collision avoidance constraints, which increases the difficulty of optimizing the control input in the MPC framework. Therefore, this study presents a method to improve the performance and computational efficiency of MPC for rendezvous and docking with a nonrotating or rotating client. An ellipsoid is adopted to model the client’s keep-out zone (KOZ). Given the spherical KOZ of the servicer, an expanded ellipsoid is introduced to describe the KOZ for the center of mass of the servicer and modeled as a nonlinear constraint. The linearization method for reference points located at the expanded ellipsoid is adopted to convexify the nonlinear constraints. The reference points are adaptively determined according to the positions of the servicer, client, and expanded ellipsoidal KOZ. The resulting hyperplanes are then used to describe the collision avoidance constraints. By utilizing the aforementioned strategies, combined with the calculated reference points, an adaptive convex programming algorithm suitable for real-time implementation of MPC is derived. The performance of the proposed method is demonstrated through numerical simulations.     

模块化可重构无人机机翼结构优化方法研究

模块化可重构无人机设计工况复杂、约束多样，需要根据不同设计思想的特点研究适用的优化方法才能得到最优方案。本文开展针对多模型的同步优化方法研究，给出不同构型机翼翼根弯矩约束方法，提出多构型机翼结构前后梁弯矩比例约束下的同步优化技术，并以某模块化可重构无人机机翼为对象进行应用验证。结果表明：与文献中模块化机翼优化结果相比，本文多构型机翼结构同步优化方法在解决整机翼更换的模块化可重构机翼结构优化问题时具有很高的适用性和收敛性，以及广阔的工程推广价值。     

状态/输入约束下飞-推一体化的保性能安全控制

基于飞行-推力一体化思想提出了一种针对搭载超燃冲压发动机的吸气式高超声速飞行器速度通道的状态/输入约束自适应鲁棒保性能安全控制方案。首先根据超燃冲压发动机的机理分析与计算流体动力模型数据，建立了安全子系统与性能子系统面向控制的仿射非线性模型。之后基于障碍Lyapunov理论与动态面设计方法设计了一套安全子系统状态约束控制器，从理论上保证了飞行器在跟踪指令的全过程中，发动机相关状态不会触碰安全边界，并结合自适应技术与辅助系统提高了该控制系统的鲁棒性。针对性能子系统设计了一套鲁棒自抗扰控制器，达到“保证安全的前提下不折损性能”的目的。仿真结果表明所设计的控制系统可以在保障安全的同时达到预想的性能，并显著放宽了超燃冲压发动机对飞行器飞行姿态的约束，保证了高超声速飞行器的机动灵活性。     

Collaborative optimization design of process parameter and structural topology for laser additive manufacturing

High-resolution laser additive manufacturing (LAM) significantly releases design freedom, promoting the development of topology optimization (TO) and advancing structural design methods. In order to fully take advantage of voxelated forming methods and establish the quantitative relationship between the mechanical properties of printing components and multiple process factors (laser- and process- parameters), the concurrent optimization design method based on LAM should cover the process-performance relationship. This study proposes a novel artificial intelligence-facilitated TO method for LAM to concurrently design microscale material property and macroscale structural topology of 3D components by adopting heuristic and gradient-based algorithms. The process–structure–property relationship of selective laser sintering is established by the back propagation neural network, and it is integrated into the TO algorithm for providing a systematic design scheme of structural topology and process parameter. Compared with the classical optimization method, numerical examples show that this method is able to improve the mechanical performance of the macrostructure significantly. In addition, the collaborative design method is able to be widely applied for complex functional part design and optimization, as well as case studies on artificial intelligence-facilitated product evaluation.