一种多协议自适应网关的应用实现

针对复杂工业生产流程控制系统中的异构网络通讯问题,设计了一种多协议自适应网关,网关采用STM32F407ZGT6芯片作为主板芯片,COMX模块作为Profibus-DP、Device Net、Ether Net/IP等协议的通讯接口,能够解决由于通讯协议不同而对系统集成产生障碍的设备。设计实现了3种典型应用,将多协议自适应网关应用于系统的集成,将不同通讯协议的控制器、执行器和现场仪表集成为一个系统,进而实现控制要求;将其应用于大型工厂的一体化,使几套不同厂家的DCS相互通讯,实现了"异构网络主站服务器"的功能;将其应用于S7-300 PLC系统中,实现了Profibus-DP接口的从站地址自适应功能。经过测试与实际应用,多协议自适应网关解决了异构网络通讯问题。     

Aero-optic imaging deviation prediction based on ISSA-ELM

When the aircraft is moving at high speed in the atmosphere, aero-optical imaging deviation will appear due to the influence of aero-optical effect. In order to achieve real-time compensation during the flight of the aircraft, it is necessary to analyze and predict the obtained imaging deviation data. In order to improve the search speed and accuracy of the prediction algorithm and the ability to jump out of local optimum, in this paper, an improved sparrow search algorithm optimized extreme learning machine (ISSA-ELM) neural network model is proposed to predict the aero-optical imagine deviation. Finally, the performance of ISSA-ELM, ELM neural network and SSA-ELM neural network was tested. The results showed that compared with ELM and SSA-ELM algorithms, the convergence speed of ISSA-ELM was significantly enhanced, and the accuracy of data prediction was also significantly improved.     

Computation and analysis of aero-optic imaging deviation of a blunt nosed aircraft with Mach number 0.5—3

Aero-optic imaging is a kind of optical effect, which describes the imaging deviation on the imaging plane. In this paper, the effect of the change of Mach number of blunt aircraft on the aero-optic imaging deviation is studied. The imaging deviations of Mach number 0.5—3 are analyzed systematically. The results show that with the increase of Mach number, imaging deviation increases gradually, and the increase rate is gradually slow. Imaging deviation slope decreases gradually with the increase of Mach number, and gradually tends to be zero, suggesting that imaging deviation is not sensitive to the change of the larger Mach number. In other words, the Mach number of smaller changes can lead to larger imaging deviation. As the Mach number of the aircraft increases, the slope of the imaging offset tends to be closer and closer to 0. When the Mach number of the aircraft increases to a certain extent, the change of the imaging offset will not have much influence. Therefore, in order to reduce the impact of flight speed on imaging migration, the aircraft should fly at a higher Mach number.     

基于分离参数标定的鱼眼镜头成像模型研究

鱼眼图像具有大视场角,但在应用方面存在严重畸变,为了探索鱼眼镜头的成像规律,本文提出一种基于分离参数标定的鱼眼镜头成像模型研究方法。对相机的物理参数进行分离标定,设计靶标,拟合径向、切向畸变系数,从而得到鱼眼镜头成像模型。比较由成像模型反推出的物点与真实物点的位置,实验结果表明,经本文提出的成像模型得到的成像点与真实物点的入射角和偏移角的误差均值分别为0.011 5和0.019 4。采用基于分离参数标定的鱼眼镜头成像模型研究方法可以较好地反映鱼眼镜头的成像规律,为更广泛地应用鱼眼镜头奠定基础。     

Empirical study of open source software selection for adoption,based on software quality characteristics

Currently, open source software (OSS) products have started to become popular in the market as an alternative to traditional proprietary or closed source software. Governments and organizations are beginning to adopt OSS on a large scale and several governmental initiatives have encouraged the use of OSS in the private sector. One major issue for the government and private sector is the selection of appropriate OSS. This paper uses new internal quality characteristics for selecting OSS that can be added to the dimensions of DeLone and McLean information systems’ model. Through this study, the quality characteristics are organized in a two level hierarchy, which list characteristics and sub-characteristics that are interconnected with three main dimensions: system quality, information quality and service quality. These characteristic dimensions are tailored to the criteria having been built from literature study and standard for software quality and guidelines. This paper presents case study results of applying the proposed quality characteristic on eight different open source software that are divided between open source network tools and learning management systems.     

基于细胞免疫的红外图像分割算法及FPGA实现

在工业生产中,高温蒸汽管道通常被用于输送高温蒸汽、高温工业废水等,但为了安全,管道通常被放置在环境比较复杂的地方,不利于工人对管道的检测与维护。快速地定位复杂背景下蒸汽管道的位置并对周围环境进行区分,已经成了一个亟待解决的问题。由于最大类间方差（Otsu）算法不能满足上述要求,基于细胞免疫机制提出了一种改进的Otsu算法,该算法通过红外图像中管道以及复杂背景的特征,能够计算出两个不同的阈值并将其分别用于图像中管道的提取与复杂背景的区分。借助QuartusⅡ软件搭建了基于FPGA的软硬件系统平台,实现了数据通信传输,并对改进的Otsu算法进行验证。实验结果表明,该算法应用在红外管道图像中能取得较好的效果。与几种边缘检测算子和经典Otsu算法相比,无论是在管道的分割,还是复杂背景的区分,本文算法都具有较高的真阳率(True Positive Rate, TPR)和较低的假阳率(False Positive Rate, FPR)。     

A Wear Model of Plane Sliding Pairs Based on Fatigue Contact Analysis of Asperities

Wear modeling is essential to predict and improve wear resistance of machine parts. This article presents a fatigue wear model of plane sliding pairs under dry friction. The wear model is constructed through developing a dynamic contact model of surfaces and proposing a mean fatigue damage constant of asperities. It is simpler and more practical than existing fatigue wear models because it describes the quantitative relationship between the wear behaviors of the plane sliding pairs and the main factors including the load and sliding speed, material property, friction property, and surface topography of the pairs. Furthermore, the wear model can predict the wear of each component of the sliding pairs. Reasonability and applicability of the wear model are validated via pin-on-disc wear tests. The wear model is applicable to predict the wear of the plane sliding pairs, which is characterized by friction fatigue of contact surfaces. The wear model can also be used to guide the tribological design of sliding pairs in machinery.     

Infrared Image Extraction Algorithm Based on Adaptive Growth Immune Field

Neural Processing Letters - In criminal investigation, there are hidden traces that many people can’t find, so infrared image is becoming an effective means to obtain these scene traces. The...     

Simultaneous displacement measurement method of multiple targets based on laser self-mixing interference

In order to simultaneously measure the displacements of multiple targets, the laser self-mixing interference(SMI) measurement method based on variational mode decomposition(VMD) is proposed. The SMI signal containing the motion information of the external targets is detected by a photodiode. The VMD can non-recursively decompose the mixed SMI signal into SMI signals corresponding to different external targets. The displacement signals can be reconstructed by fringe counting method and interpolation method. The experimental results show that the displacement signals of different external targets can be reconstructed with half wavelength accuracy, which verifies the correctness and feasibility of this method. This method can improve the measurement efficiency, which offers an effective method for the multi-channel displacement measurement.     

基于多特征融合的红外图像分类研究

针对传统红外图像目标分类方法准确率低的问题,提出了一种用结合多特征融合的粒子群优化(Particle Swarm Optimization, PSO)算法来优化支持向量机(Support Vector Machine, SVM)的方法。该方法采用方向梯度直方图(Histogram of Oriented Gradient, HOG)和局部二值模式(Local Binary Pattern, LBP)两类特征描述红外图像中目标的轮廓特征和局部纹理,从不同的方面展现红外图像的特点,在图像的特征表达上具有一定的互补性。在特征提取后对样本数据进行凸包算法计算,得到一些具有代表性的样本数据,从而提高分类计算效率;在分类模型训练时,采用PSO算法优化SVM,寻找SVM的最优惩罚因子和核参数,从而提高分类模型的准确率。实验结果表明,多特征融合的分类模型的准确率比单一特征的分类模型提高近10%,且经PSO优化的SVM最终模型的分类准确率高达99%。