Optimal Design of Novel Electromagnetic-Ring Active Balancing Actuator with Radial Excitation

Imbalance vibration is a typical failure mode of rotational machines and has significant negative effects on the effii-ciency,accuracy,and service life of equipment.To automatically reduce the imbalance vibration during the opera-tional process,different types of active balancing actuators have been designed and widely applied in actual produc-tion.However,the existing electromagnetic-ring active balancing actuator is designed based on an axial excitation structure which can cause structural instability and has low electromagnetic driving efficiency.In this paper,a novel radial excitation structure and the working principle of an electromagnetic-ring active balancing actuator with a combined driving strategy are presented in detail.Then,based on a finite element model,the performance param-eters of the actuator are analyzed,and reasonable design parameters are obtained.Self-locking torque measurements and comparative static and dynamic experiments are performed to validate the self-locking torque and driving effi-ciency of the actuator.The results indicate that this novel active balancing actuator has sufficient self-locking torque,achieves normal step rotation at 2000 r/min,and reduces the driving voltage by 12.5％.The proposed novel balancing actuator using radial excitation and a combination of permanent magnets and soft-iron blocks has improved electro-magnetic efficiency and a more stable and compact structure.     

Relevance- and interface-driven clustering for visual information retrieval

Search results of spatio-temporal data are often displayed on a map, but when the number of matching search results is large, it can be time-consuming to individually examine all results, even when using methods such as filtered search to narrow the content focus. This suggests the need to aggregate results via a clustering method. However, standard unsupervised clustering algorithms like $K$-means (i) ignore relevance scores that can help with the extraction of highly relevant clusters, and (ii) do not necessarily optimize search results for purposes of visual presentation. In this article, we address both deficiencies by framing the clustering problem for search-driven user interfaces in a novel optimization framework that (i) aims to maximize the relevance of aggregated content according to cluster-based extensions of standard information retrieval metrics and (ii) defines clusters via constraints that naturally reflect interface-driven desiderata of spatial, temporal, and keyword coherence that do not require complex ad-hoc distance metric specifications as in $K$-means. After comparatively benchmarking algorithmic variants of our proposed approach – RadiCAL – in offline experiments, we undertake a user study with 24 subjects to evaluate whether RadiCAL improves human performance on visual search tasks in comparison to $K$-means clustering and a filtered search baseline. Our results show that (a) our binary partitioning search (BPS) variant of RadiCAL is fast, near-optimal, and extracts higher-relevance clusters than $K$-means, and (b) clusters optimized via RadiCAL result in faster search task completion with higher accuracy while requiring a minimum workload leading to high effectiveness, efficiency, and user satisfaction among alternatives.     

基于数值微分核脉冲信号数字处理方法

核反应堆核测量系统测量探测器输出的核脉冲信号，该信号后沿拖尾很长，在计数率较高时容易产生信号堆积和基线漂移等问题，导致源区计数率测量上限仅能达到105 Hz左右。文中基于数值微分方法，采用数字处理技术，在时域上分析了核脉冲信号经过前置放大、信号成形、低通滤波和脉冲甄别后的输出，并利用探测器实测信号进行了仿真。仿真结果表明，基于数值微分的数字处理方法可以实现相邻0.4 μs脉冲信号的识别和测量，将源区测量计数率上限提升到2×106 Hz以上。      

Structural load alleviation using distributed delay shaper: Application to flexible aircraft

Lightweight flexible aircraft suffers from unwanted oscillatory vibrations during aircraft manoeuvres. A recently developed distributed-delay signal (DZV) shaper is therefore proposed to be applied as a feedforward controller to alleviate the manoeuvre loads, as an alternative to traditional structural filters used routinely in this context. Structural filters are essentially linear low-pass filters with bandwidth below the significant flexible modes, applied to control signals generated either by the pilot’s direct input or by the flight control system. It has been showed that if instead a properly tuned signal shaper is used, better performance can be achieved: first, the target modes are significantly attenuated while the responsiveness of the aircraft is less compromised and secondly, the oscillatory nature of the vibrations are reduced. The high fidelity simulation results on a full scaled dynamic model of a highly flexible blended wing–body (BWB) aircraft show that in comparison to traditional structural filters, signal shapers significantly reduce the wing root loading (forces and moments) which provides potential structural benefits.     

A mechanism based on finger-sliding behavior for designing radial menus

Human behavior about sliding their fingers on touch screens needs to be understood for the design of radial menus. For this purpose, data about the angles of finger sliding in performing radial pointing to eight predefined directions were collected. The optimal angle ranges and boundaries for these directions were then determined by the proposed mechanism. Consistent with previous research, results showed that the deviations of slide angles for the four diagonal directions were larger than that for the four orthogonal directions. Therefore, to reduce overall pointing errors, the angle ranges for the diagonal directions should be wider than that for the orthogonal directions. Based on the proposed mechanism, the total probability of pointing errors could be limited to 0.05%, compared to the error of 2.00% if the eight angle ranges were evenly divided by the radii of a regular octagon. Besides the angles, the lengths and starting points of the slides were reported and discussed along with the oblique effect, judder effect, and screen orientation. Possible applications of the proposed mechanism for dynamic and personalized radial menus are addressed. Further research would be worthwhile to examine the effects of screen orientation and the number of predefined directions on pointing performances. Moreover, extending the research to mid-air sliding gestures would be of interest and value in designing three-dimensional radial menus.Relevance to industryThe proposed mechanism could effectively enhance the accuracy of the selections through radial menus, and could be applied to the remote controls via smart handheld devices.     

矿区铁路车站信号联锁系统核心设备换型升级关键技术研究

传统的信号联锁系统改造采用室内设备全部更换的方式,投资预算较高。为确保铁路运输安全,维护铁路生产运输秩序,提高信号设备的安全性,同时为减轻现场技术人员管控压力,研究应用新的技术方法,仅对室内信号联锁系统核心设备进行换型升级,室内相关配套设备不做更换,同样能够达到技术改造的效果,满足技术指标需求,同时可以节约大量资金投入。因此,本文针对上述问题开展信号联锁系统核心设备换型升级关键技术研究并在矿区铁路跃进河车站应用,效果显著。     

Development of silicon wafer packaging technology for deep UV LED

This paper reports a deep‐ultraviolet LED (deep‐UV‐LED) package based on silicon MEMS process technology (Si‐PKG). The package consists of a cavity formed by silicon crystalline anisotropic etching, through‐silicon vias (TSVs) filled with electroplated Cu, bonding metals made of electroplated Ni/AuSn and a quartz lid for hermetic sealing. A deep‐UV LED die is directly mounted in the Si‐PKG by AuSn eutectic bonding without a submount. It has advantages in terms of size, heat dissipation, light utilization efficiency, productivity and cost over conventional AlN ceramic packages. We confirmed a light output of 30 mW and effective reflection on Si (111) cavity slopes in the Si‐PKG. Based on simulation, further improvement of the optical output is expected by optimizing DUV‐LED die mount condition.     

Parameter identification of proton exchange membrane fuel cell via Levenberg-Marquardt backpropagation algorithm

It is essential to develop an accurate model of proton exchange membrane fuel cell (PEMFC) for a reliable operation and analysis, in which unknown parameters usually need to be determined. The inherent nonlinear, strong coupling, and diversification of PEMFC model seriously hinder traditional methods to identify the parameters. For the sake of overcoming these thorny obstacles, Levenberg-Marquardt backpropagation (LMBP) algorithm based on artificial neural networks (ANNs) is proposed for PEMFC parameter identification. Furthermore, the performance of LMBP is thoroughly evaluated and compared with four typical meta-heuristic algorithms under three cases. Simulation results indicate that LMBP performs a higher accuracy and faster speed for parameter identification. In particular, accuracy and convergence speed can achieve as much as 99.8% and 95.9% growth via LMBP, respectively.     

Tuning of Active Disturbance Rejection Control with application to power plant furnace regulation

Active Disturbance Rejection Control (ADRC) is emerging as a promising solution in dealing with the unmeasurable disturbances and unknown uncertainties, which are treated in a lumped manner and augmented as an extended state variable. Subsequently, an extended state observer (ESO) is designed to estimate and cancel the combined uncertain term in real time, modifying the uncertain plant to behave like a nominal model consisting of integrators. In the original ADRC formulation, the plant model is assumed to be of delay-free and its order is assumed to be equal to that of the real plant. However, a low-order ADRC is preferred and received a wide acceptance in practice because of its simplicity. Currently, the feasibility of such practice is not clearly revealed as well as its potential dangers. To this end, this paper analyzes the control mechanism from the perspective of the modified plant, which, in turn, would give guidance to parameter tuning. The effect of each parameter on the compensation efficiency and stability conditions of the modified plant is analyzed, based on which a complete tuning procedure for ADRC is developed where the initial settings is derived from the existing PI controller parameters. Finally, the proposed tuning method is experimentally used for a furnace pressure regulation of a 1000MW power plant, validating the feasibility of the low-order ADRC, even in the absence of both dynamic model and the information on the model order.     

Synchroextracting chirplet transform for accurate IF estimate and perfect signal reconstruction

Synchroextracting transform (SET) is a recently developed time-frequency analysis (TFA) method aiming to achieve a highly concentrated TF representation. However, SET suffers from two drawbacks. The one is that SET is based upon the assumption of constant amplitude and linear frequency modulation signals, therefore it is unsatisfactory for strongly amplitude-modulated and frequency-modulated (AM-FM) signals. The other is that SET does not allow for perfect signal reconstruction, which leads to large reconstruction errors when addressing fast-varying signals. To tackle these problems, in this paper, we first present some theoretical analysis for the SET method, including the existence of the fixed squeeze frequency, the performances of the instantaneous frequency (IF) estimator and the SET reconstruction. Then, a new TFA method, named synchroextracting chirplet transform (SECT), is proposed, which sharpens the TF representation by extracting the TF points satisfying IF equation, and retains an excellent signal reconstruction ability. Numerical experiments on simulated and real signals demonstrate the effectiveness of the SECT method.