Memory-based dynamic event-triggered control for networked interval type-2 fuzzy systems subject to DoS attacks

In this article, the memory-based dynamic event-triggered controller design issue is investigated for networked interval type-2 (IT2) fuzzy systems under non-periodic denial-of-service (DoS) attacks. For saving limited network bandwidth, a novel memory-based dynamic event-triggered mechanism (DETM) is proposed to schedule data communication. Unlike existing event-triggered generators, the developed memory-based DETM can utilize a series of newly released signals and further save network resources by introducing interval dynamic variables. Moreover, to improve design flexibility, an IT2 fuzzy controller with freely selectable fuzzy rule number and premise membership functions (MFs) is synthesized. Then, a new switched time-delay system with imperfectly matched MFs is established under the consideration of memory-based DETM and DoS attacks simultaneously. Besides, based on the property of MFs, the boundary information of membership grades and slack matrices are introduced in the stability analysis. Furthermore, by using a piecewise Lyapunov–Krasovskii method, membership-functions-dependent criteria are deduced to ensure the asymptotic stability of built fuzzy switched systems. Finally, the effectiveness of proposed control strategies is demonstrated by simulation examples.     

基于LP与小波包的复杂机电系统监测序列混沌降噪方法

针对流程工业生产系统监测数据存在强噪声和混沌性的特点,提出了一种局部投影方法(Local Projection Method)与小波包方法相结合的信号降噪方法。该方法先利用局部投影方法从动力学系统嵌入流形的角度进行多次迭代降噪,并根据关联维数来判定迭代终止;再利用小波包方法从频率的角度进行降噪,抑制高频噪声的干扰,取得了较好的降噪效果。用Lorenz时间序列进行仿真验证,对仿真时间序列加入不同程度的噪声,对比分析小波包、局部投影与该方法降噪后的相空间、SNR值和最大Lyapunov指数,证明了该方法对于中高强度噪声具有更好的降噪效果。并将该方法用于某压缩机组的实际监测数据降噪,评估三种方法的降噪效果,进一步验证了该方法的优越性。     

An interval observer for uncertain continuous‐time linear systems

To design robust interval observers for uncertain continuous‐time linear systems, a new set‐integration approach is proposed to compute trajectory tubes for the estimation error. Because this approach, the order‐preserving condition on the dynamics of the estimation error is no longer required. Therefore, synthesis methods can be used to compute observer gains that reduce the impact of the system uncertainties on the accuracy of the estimated state enclosures. The performance of the proposed approach is showcased through illustrative numerical examples.     

Q值正演模拟约束下的零偏移距VSP资料Q值估算

随着油气勘探目的层逐步走向深部,球面扩散、透射损失、环境噪声等使得VSP资料的初至子波发生改变,导致常规的Q值估算方法质量难以得到保证。为此,利用塔里木盆地托甫台地区TP327井零偏移距VSP资料,综合考虑透射损失和球面扩散的影响,提出一种Q值正演模拟约束下的零偏移距VSP资料Q值估算方法。该方法通过研究区的纵波速度、横波速度和密度建立层状地质模型,利用射线追踪的方法,用大地吸收介质模型的Q值正演模拟结果,对频谱比法和经验公式估算的初始Q值进行修正,使得Q值正演模拟结果与实际地震波的衰减记录在频谱特征上吻合,从而得到更为精确的Q模型。TP327井Q值估算结果表明,该方法与李庆忠经验公式得到的结果在浅层比较接近,但在中层和深层,两者差异较大;Q值正演模拟结果约束的子波与实际VSP资料子波的频谱比较吻合,证实用Q值正演模拟约束得到的层间Q值更为可靠。利用Q值正演模拟约束方法得到的Q模型对研究区地震资料进行反Q滤波能显著提高地震资料分辨率,有助于提高碳酸盐岩地层中缝洞的识别精度。     

砂砾岩体沉积期次划分及其与物性的关系——以东营凹陷北部陡坡带Y920区块沙四上亚段为例

砂砾岩体储层岩性复杂、非均质性强，且扇体多期叠置，沉积期次划分困难。以东营凹陷北部陡坡带Y920区块沙四上亚段砂砾岩体为研究对象，建立以岩心、FMI图像为基础，以测井信息小波变换技术为核心，以三维地震为约束的砂砾岩扇体沉积期次划分方法。基于岩心、FMI图像可直观识别沉积期次界面，进而标定常规测井资料；经测井信息小波变换后表现出周期性振荡特征的小波系数曲线可反映沉积界面响应特征，结合功率谱筛选尺度因子，可定量对单井沉积期次进行划分；通过井-震结合，实现全区域期次界面的等时对比，将Y920区块砂砾岩体划分为8个沉积期次。沉积期次的发育控制着沉积相及岩性的分布，与物性展布也密切相关。研究结果表明，研究区块地层自下而上（8至1沉积期次）表现出退积沉积初始阶段（扇根—扇中）沉积期次中上部物性较好，沉积中间阶段（扇中）整个沉积期次物性均较好，而沉积末期阶段（扇中—扇端）沉积期次中下部物性较好，进而统计单井各期次有效储层的厚度，分期次刻画有效储层平面展布特征，发现3，4，5沉积期次的西北部为Y920区块有利储层展布范围。研究结果为东营凹陷北部陡坡带砂砾岩体油藏的精细勘探开发提供了依据。     

准噶尔盆地南缘四棵树地区中浅层砾岩层识别刻画

准噶尔盆地南缘中、下组合构造普遍位于中浅层砾岩层之下,砾岩层具有横向展布范围广且不规则、纵横向速度变化大等特点,严重制约中、下组合目标的精细落实。因此,搞清砾岩层结构及分布特征,对下伏构造形态和高点位置的准确落实尤为重要。结合微测井、钻井、测井资料以及地震剖面对准噶尔盆地南缘四棵树地区中浅层砾岩层结构特征进行分析,对低速和高速砾岩层的顶底界面进行识别刻画,并分区、分段建立了砾岩层时深关系曲线,用于指导深度域下组合构造成图和叠前深度偏移中浅层速度模型的建立。实例应用证明,南缘四棵树地区中浅层砾岩层识别刻画对准确落实构造目标,提高地震剖面成像品质至关重要,同样也可以在准噶尔盆地南缘其他类似地区进行推广应用。     

Location Related Signals with Satellite Image Fusion Method Using Visual Image Integration Method

Investigations were performed on a group utilizing (General Purpose Unit) GPU and executions were evaluated for the utilization of the created parallel usages to process satellite pictures from satellite Landsat7.The usage on a realistic group gives execution change from 2 to 18 times. The nature of the considered techniques was assessed by relative dimensionless global error in synthesis (ERGAS) and Quality Without Reference (QNR) measurements. The outcomes demonstrate execution picks ups and holding of value with the bunch of GPU contrasted with the outcomes and different analysts for a CPU and single GPU. The errand of upgrading the view of a scene by combining data caught from various picture sensors is usually known as multisensor picture combination. This paper displays a territory based picture combination calculation to consolidate SAR (Synthetic Aperture Radar) and optical pictures. The co-enlistment of the two images is first led utilizing the proposed enrollment method prior to picture combination. The paper displays a parallel execution of existing picture combination techniques on a graphical group. Parallel executions of techniques in view of discrete wavelet changes are created. Division into dynamic and motionless regions is then executed on the SAR surface picture for particular injection of the SAR picture into panchromatic (PAN) picture. An integrated image in view of these two pictures is produced by the novel region based combination plot, which forces diverse combination rules for each fragmented region. At long last, this picture is melded into a multispectral(MS) picture through the half breed skillet honing technique proposed in past research. Exploratory outcomes exhibit that the proposed strategy demonstrates preferred execution over different fusion algorithms and can possibly be connected to the multisensory combination of SAR and optical pictures.     

基于S变换的高速列车小幅蛇行识别方法

针对现有的高速列车监测方法没有考虑高速列车振动信号的非平稳特性,从而使得列车出现蛇形失稳现象的问题，提出一种采用S变换的方法对高速列车转向架信号进行处理，进而提取高速列车运行特征。采用最小二乘支持向量机（LS-SVM）对特征进行训练和识别，结果证明，基于S变换的特征提取方法的识别准确率达到了100%，优于基于小波变换的特征提取方法，从而可以及时预测高速列车的运行状态，保障列车的运行安全。     

Visually deficient working conditions and reduced work performance in office workers: Is it mediated by visual discomfort?

IntroductionThe main purpose of this cross-sectional study was to investigate whether visual discomfort acts as a mediating factor between perceived visual ergonomic working conditions and self-rated visual performance among office workers who carry out administrative tasks and computer-based work at the Swedish Tax Agency.MethodsA questionnaire was sent to 94 office workers addressing: 1) perceived visual quality of the visual display units; 2) prevalence of eye symptoms; and 3) self-rated visual performance. Eighty-six persons (54 women (63%), 31 men (36%), and 1 of unspecified sex) answered the questionnaire. Multiple regression analysis investigated the association between visual ergonomic working conditions and visual performance, both with and without visual discomfort as a mediator.ResultsThe group mean of the Indexed survey questions indicated a reasonably good quality of visual ergonomic working conditions, a relative absence of eye symptoms, and acceptable self-rated visual performance. Results from multiple regression analysis showed a significant association between perceived visual ergonomic working conditions and self-rated visual performance (r² = 0.30, β = 0.327, p < 0.01). When visual discomfort was used as a mediator, the association between perceived visual ergonomic working conditions and self-rated visual performance remained the same (r² = 0.32, β = 0.315, p < 0.01).DiscussionIt was remarkable to discover that self-rated visual performance was independent of visual discomfort. Possible explanations include exposure factors not included in the current study, such as dry air and sensory irritation in the eyes, psychosocial stress, time spent performing near work activities, or time exposed to visually deficient working conditions.Relevance to industryThe strong connection between satisfaction with visual ergonomic working conditions and productivity in this study has implications for workplace profitability and staff satisfaction. If productivity is enhanced by better visual ergonomic working conditions, then managers of workplaces may be able to improve work outcomes by optimizing the physical work environment.     

Multi-objective iterative optimization algorithm based optimal wavelet filter selection for multi-fault diagnosis of rolling element bearings

Rolling element bearings (REBs) play an essential role in modern machinery and their condition monitoring is significant in predictive maintenance. Due to the harsh operating conditions, multi-fault may co-exist in one bearing and vibration signal always exhibits low signal-to-noise ratio (SNR), which causes difficulties in detecting fault. In the previous studies, maximum correlated kurtosis deconvolution (MCKD) has been validated as an efficient method to extract fault feature in the fault signals. Nonetheless, there are still some challenges when MCKD is applied to fault detection owing to the rigorous requirements of multiple input parameters. To overcome limitation, a multi-objective iterative optimization algorithm (MOIOA) for multi-fault diagnosis is proposed. In this method, correlated kurtosis (CK) is taken as a criterion to select optimal Morlet wavelet filter using the whale optimization algorithm (WOA). Meanwhile, to further eliminate the effect of the inaccurate period on CK, the update process of period is incorporated. After that, the simulated and experimental signals are utilized to testify the validity and superiority of the MOIOA for multiple faults detection by the comparison with MCKD. The results indicate that MOIOA is efficient to extract weak fault features even with heavy noise and harmonic interferences.