在CodeWarrior编译环境下运行μC／OS—Ⅲ

μC／OS-Ⅱ是面向8／16位及低端32位单片机应用的RTOS,而新近推出的μC／OS-Ⅲ则面向高性能32位单片机,如ARMCortex等。以Cortex—M4为内核的Kinetis系列单片机,不仅用于全国大学生飞思卡尔杯智能车竞赛,也用于诸多大学的嵌入式系统教学,官方提供的开发环境是CodeWarrior。本文介绍如何利用CodeWarrior开发环境,将μC／OS-Ⅲ在Kinetis单片机上运行起来,以便将μC／OS-Ⅲ引入教学、科研与应用。     

漫射红外技术的智能家居无线局域网设计

分析了红外技术在短距离无线通信中的优势,并将其应用在智能家居局域网中;结合安华高科技公司的HSDL-3020红外收发模块搭建了硬件电路,构成网络的主从节点;介绍了网络组建的过程,包括IrDA协议栈结构、数据编码格式、链路连接、网络管理机制等。本设计实现了对家居设备的统一管理,具有较高的应用价值。     

A new admissibility condition of discrete-time singular systems with time-varying delays

This paper gives a novel delay-dependent admissibility condition of discrete-time singular systems with time-varying delays. For convenience, the time-varying delay is assumed to be the sum of delay lower bound and the integral multiples of a constant delay. Specially, if the constant delay is of unit length, the delay is an interval-like time-varying delay. The proposed admissibility condition is presented and expressed in terms of linear matrix inequality (LMI) by Lyapunov approach. Generally, the uncertainty of time-varying delay would lead to conservatism. In this paper, this critical issue is tackled by accurately estimating the time-varying delay. Consequently, the proposed admissibility condition is less conservative than the existing results, which is demonstrated by a numerical example.     

Data preprocessing using hybrid general regression neural networks and particle swarm optimization for remote terminal units

Data corruption in SCADA systems refers to errors that occur during acquisition, processing, or transmission, introducing unintended changes to the original data. In SCADA-based power systems, the data gathered by remote terminal units (RTUs) is subject to data corruption due to noise interference or lack of calibration. In this study, an effective approach based on the fusion of the general regression neural network (GRNN) and the particle swarm optimization (PSO) technique is employed to deal with errors in RTU data. The proposed hybrid model, denoted as GRNN-PSO, is able to handle noisy data in a fast speed, which makes it feasible for practical applications. Experimental results show the GRNN-PSO model has better performance in removing the unintended changes to the original data compared with existing methods.     

Study on heat conduction and adsorption/desorption characteristic of MIL-101/few layer graphene composite

Journal of Porous Materials - Aiming at the poor heat conduction performance of porous MIL-101 applied in adsorption cooling process, few layer graphene (FLG) was selected as a promising thermal...     

焊接热源有效利用率的测试计算法

给出实际热输入值是正确求解焊接热弹塑性问题和焊接残余应力与变形问题的前提;因而,准确地确定热源有效利用率η,在焊接力学的发展中是一个急待解决的命题。本文推荐采用的“测试计算法”提供了一个能够准确、简捷地求得η值的新途径。引入被焊材料的熔化潜热系数后,给出了线热源加热焊缝金属至熔化温度(处于液态)时的实际热有效利用率ηt 的表达式。在四种不同类型的薄板材料上进行了钨极氩弧焊试验,测试计算结果与理论值相符合。理论推导与试验结果均证明,形成焊缝所需要的线能量的无量纲数值等于焊缝金属熔化热有效利用率ηt 的倒数。文中给出的焊接规范参数选择原则也适用于符合线热源条件的其它熔焊热源。η值不但与焊接工艺方法、规范参数有关,而且也随被焊材料的热物理特性不同而异。     

挤压变形对Mg95Zn4.3Y0.7合金组织和性能的影响

研究了在250℃、不同挤压比下挤压变形对Mg95 Zn4.3 Y0.7合金组织及性能的影响。结果表明，Mg95 Zn4.3 Y0.7经过挤压变形后，合金中晶界处的共晶相破碎，弥散分布至晶粒内部，并且晶粒显著细化。同时，随着挤压比的增大，晶粒细化程度增加，合金的力学性能单调增加。当挤压比为16时，合金晶粒尺寸为5-8μm，抗拉强度为288.9MPa，显微硬度HV值为117.8。     

长轴表面激光淬火变形与控制

应用激光淬火强化技术控制长轴的淬火变形，分析了激光淬火变形的原因和影响因素。研究结果表明，激光淬火不仅可使长轴振摆变形量控制在很小的范围内，而且可将已变形的长轴校直到很高的精度。     

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.     

PAN/FPU Composite Nanofiber Membrane with Superhydrophobic and Superoleophobic Surface as a Filter Element for High-Efficiency Protective Masks

Recently, because of the outbreak of COVID-19, the demand for various types of filter elements in protective materials has increased globally. Furthermore, new requirements for the filtration performance of PM2.5 liquid (oil) particles have been put forward. In this work, Superhydrophobic and superoleophobic composite nanofibers with excellent filtration capacity for oil and salt particles are developed through the modification of polyacrylonitrile (PAN) by fluoro-polyurethane (FPU) doping. The results show that the PAN/FPU composite nanofibers doped with 9 wt% FPU has a uniform fiber morphology with a diameter of 240 ± 30 nm. Compared to the pure PAN nanofibers, the water-based contact angle of PAN/FPU increases from 90 ± 5° to 151 ± 5°, and the oil-based contact angle increases from 58 ± 2° to 152 ± 3°. Importantly, at a high flow rate of 95 L min⁻¹, the filtration efficiency of the PAN/FPU nanofiber membrane for 0.3 µm oil particles increases from 92 ± 1% to 99.2 ± 0.1%. After cyclic loading, the filtration efficiency of 0.3 µm oil particles remains above 98%. Meanwhile, the filtration efficiency for 0.3 µm salt particles remains at 98.23 ± 0.1%. The PAN/FPU nanofiber membrane developed in this work is effective in applications and has good market prospects as a protective filtration material.