应用加权中值滤波法检测薄壁梁式挠性器件下摆量

应用加权中值滤波法对薄壁梁式挠性器件下摆量进行高准确度CCD检测。薄壁梁式挠性器件在测量过程中测量图像存在高频抖动现象,因此测量准确度不高,运用加权中值滤波后使用最小二乘法细分技术,可以在实现提高测量准确度的同时,消除高频抖动带来的误差,从而可以有效提高CCD测量薄壁梁式挠性器件下摆量的准确度。实验表明,该方法比传统测量方法准确度提高20倍以上。     

Online scheduling of distributed Earth observation satellite system under rigid communication constraints

This paper focused on online scheduling of distributed Earth observation satellite system in a dynamic environment. The objective was to maximize the total profit of the overall system by efficiently coordinating the different satellites with stochastic arrival of urgent tasks, subject to rigid communication and observation time window constraints. We formulated this problem as a single-task, single-robot, time-extended assignment problem with intra-schedule dependency using the multi-robot task assignment taxonomy and formulated the sub-problem after releasing urgent tasks in a mixed-integer linear programming model. We first described the online scheduling algorithm for a single satellite, then we proposed the modified consensus-based bundle algorithm (m-CBBA) and modified asynchronous consensus-based bundle algorithm (m-ACBBA) with synchronous and asynchronous communication, respectively. Compared with initial versions of CBBA and ACBBA, the modified versions added the communication loop prediction phases to efficiently utilize scarce communication opportunities and reduce the communication requirements. Additionally, we introduce two contract net protocol (CNP)-based algorithms for comparison, respectively SingleItem-CNP-based (SI-CNP) algorithm and Batch-CNP-based (BA-CNP) algorithm. Computational experiments indicated that both the total profit and percentage of scheduled urgent tasks achieved by the m-ACBBA and m-CBBA algorithms were much higher than those achieved by both SI-CNP and BA-CNP. Additionally, the number of communications needed by either m-ACBBA or m-CBBA algorithm was lower than that by SI-CNP. When the communication cost in the system is high, the m-CBBA algorithm is preferred because it balances the profit and the required number of communications. When the communication cost is low, the m-ACBBA algorithm is preferred because it achieves high total profit and high percentage of scheduled urgent tasks.     

Hybrid integration method for highly maneuvering radar target detection based on a Markov motion model

To detect highly maneuvering radar targets in low signal-to-noise ratio conditions, a hybrid long-time integration method is proposed, which combines Radon-Fourier Transform (RFT), Dynamic Programming (DP), and Binary Integration (BI), named RFT-DP-BI. A Markov model with unified range-velocity quantification is formulated to describe the maneuvering target’s motion. Based on this model, long-time hybrid integration is performed. Firstly, the whole integration time is divided into multiple time segments and coherent integration is performed in each segment via RFT. Secondly, non-coherent integration is performed in all segments via DP. Thirdly, 2/4 binary integration is performed to further improve the detection performance. Finally, the detection results are exported together with target range and velocity trajectories. The proposed method can perform the long-time integration of highly maneuvering targets with arbitrary forms of motion. Additionally, it has a low computational cost that is linear to the integration time. Both simulated and real radar data demonstrate that it offers good detection and estimation performances.     

Adaptive suppression of passive intermodulation in digital satellite transceivers

For the performance issues of satellite transceivers suffering passive intermodulation interference,a novel and effective digital suppression algorithm is presented in this paper.In con trast to analog approaches,digital passive intermodulation (PIM) suppression approaches can be easily reconfigured and therefore are highly attractive for future satellite communication systems.A simplified model of nonlinear distortion from passive microwave devices is established in consid eration of the memory effect.The multiple high-order PIM products falling into the receiving band can be described as a bilinear predictor function.A suppression algorithm based on a bilinear poly nomial decorrelated adaptive filter is proposed for baseband digital signal processing.In consideration of the time-varying characteristics of passive intermodulation,this algorithm can achieve the rapidness of online interference estimation and low complexity with less consumption of resources.Numerical simulation results show that the algorithm can effectively compensate the passive intermodulation interference,and achieve a high signal-to-interference ratio gain.     

双框架飞机蒙皮检测机器人切换运动控制方法

针对一种双框架飞机蒙皮检测机器人,通过分析该机器人在飞机表面上的受力情况,在飞机表面该机器人受到了非完整约束,基于牛顿-欧拉法建立了机器人非完整约束动力学模型。根据机器人机械结构和运动步态分析,将该非完整机器人系统分为子系统A和子系统B。为了实现机器人在飞机表面运动,采用反演技术和快速Terminal滑模控制相结合的思想对系统设计了控制器,提出了一种反演-滑模控制方法;对于非完整机器人子系统A和子系统B,设计了一种基于事件驱动的切换策略,实现了机器人对期望轨迹的全局渐近跟踪,并利用Lyapunov稳定性证明系统的跟踪误差收敛。仿真和试验表明,采用该切换策略和反演-滑模控制方法,双框架飞机蒙皮检测机器人可以在飞机表面自由运动并进行损伤检测,具有良好的可靠性和稳定性。     

Multi-mode diagnosis of a gas turbine engine using an adaptive neuro-fuzzy system

Gas Turbine Engines (GTEs) are vastly used for generation of mechanical power in a wide range of applications from airplane propulsion systems to stationary power plants. The gas-path components of a GTE are exposed to harsh operating and ambient conditions, leading to several degradation mechanisms. Because GTE components are mostly inaccessible for direct measurements and their degradation levels must be inferred from the measurements of accessible parameters, it is a challenge to acquire reliable information on the degradation conditions of the parts in different fault modes. In this work, a data-driven fault detection and degradation estimation scheme is developed for GTE diagnostics based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). To verify the performance and accuracy of the developed diagnostic framework on GTE data, an ensemble of measurable gas path parameters has been generated by a high-fidelity GTE model under (a) diverse ambient conditions and control settings, (b) every possible combination of degradation symptoms, and (c) a broad range of signal to noise ratios. The results prove the competency of the developed framework in fault diagnostics and reveal the sensitivity of diagnostic results to measurement noise for different degradation symptoms.     

硅半球深腔结构无损检测技术

半球深腔的加工质量是决定硅基MEMS半球陀螺精度的关键因素之一，及时检测半球深腔的形貌参数并将其反馈至加工过程，是确保高性能MEMS半球陀螺研制成功的重要措施。由于硅半球深腔的深度较大，台阶仪和光学显微成像系统无法对半球深腔的形貌特征进行有效测量。因此,需要将硅深腔结构剖开后采用扫描电镜(SEM)进行检测。这种检测方式时间周期长，且属于破坏性的样本检测，效率和测试精度都较低。提出以硅半球深腔为模具，利用PDMS铸模将硅半球深腔的结构尺寸和表面形貌转移到PDMS凸起的半球模型上，通过检测PDMS半球模型的尺寸结构和表面形貌，即可反推出硅半球深腔的尺寸特征。经实验验证，脱模后的PDMS模型可以准确地反映出半球深腔的尺寸信息，测量结果的不确定度小于5‰，有效解决了硅半球深腔无损检测的难题。     

存在外部干扰的网络控制系统故障检测和优化

针对存在时延和丢包的网络控制系统,研究了系统的故障检测滤波器设计和优化设计问题.通过泰勒展开将未知时延处理成外界干扰,采用伯努利随机过程来描述丢包现象.设计观测器产生残差信号,将故障检测问题转化为H∞滤波问题.通过Lyapunov函数方法分析了系统的稳定性.以线性矩阵不等式的形式给出了滤波器存在的充分条件和求解方法.为进一步提高系统对故障信号的灵敏度,采用了一种优化设计方法对故障检测系统进行了优化.最后通过仿真验证了算法的有效性.