共查询到17条相似文献,搜索用时 140 毫秒
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提出一种对光参量呈非单调下降规律的LED灯珠可靠性进行评价的方法.采用加速寿命实验获得光通量退化数据,利用指数叠加形式的退化模型对光通维持率退化数据进行拟合,与指数模型拟合效果相比,该模型具有更好的效果.用MATLAB软件计算样品的伪失效寿命,通过KolmogorovSmirnov检验法得到两个公司样本伪失效寿命分布分别服从对数正态分布和威布尔分布,以相应分布参量评估产品可靠性得到两个公司样本的伪失效寿命分别为5 328.37h和4 758.35h.该方法对参量呈非单调下降规律的LED器件可靠性的评估具有参考价值. 相似文献
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基于加速性能退化的LED灯具可靠性评估 总被引:2,自引:2,他引:0
提出了一种基于加速性能退化的LED灯具可靠性快速评估方法。以LED灯具的使用寿命评估为目标,设计了温度和电应力的恒定应力加速退化试验及其加速模型,给出了基于性能退化的LED灯具可靠性评估一般流程。以国内某型LED灯管为试验对象,对其可靠性进行了评价:在正常应力水平下,该型LED灯管的寿命评估值为31 571 h。结果表明该方法能够快速、有效地评估LED灯管的可靠性。该方法不仅节省实验时间,而且对LED灯具的可靠性评估及产品质量管理有一定的参考价值。 相似文献
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根据强激光能源模块高储能密度电容器在工作过程中,受到连续冲击而使退化失效具有累积效应的特点,提出了利用产品运行过程中性能参数退化的信息,用复合Poisson过程对退化轨道建模并进行可靠性评估的方法。给出了模型参数的矩估计和电容器的平均退化量、可靠度、平均寿命等可靠性指标评估的Bootstrap仿真过程。并通过实例说明了该评估方法在工程中的应用。基于电容退化信息的可靠性评估方法,可以在极少甚至没有寿命数据的情况下给出客观可信的评估结果,在理论和应用上都具有重要的价值。 相似文献
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基于金属化膜脉冲电容器的失效机理,研究了基于加速退化数据的金属化膜脉冲电容器可靠性评估问题,给出了一个该型电容器的加速退化失效模型和参数统计推断方法。基于试验数据可求得该型电容器可靠性模型中未知参数的估计值分别为9.066 9×10-8sup>和0.022 1,将该值代入失效分布函数即可确定电容器的失效模型,由此模型求得该型电容器充放电20 000次的可靠度为0.972 4。使用这种分析方式对金属化膜脉冲电容器进行可靠性分析将更能节省试验时间和费用。 相似文献
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Zoltán Ádám Tamus 《Journal of Electrostatics》2013,71(3):564-567
The condition assessment of high voltage equipment requires reliable diagnostic measurements. The reliability of an insulation diagnostic method can be examined by accelerated laboratory tests besides the analysis of failure statistics. Laboratory tests are used to find appropriate diagnostic method to insulation or insulating material. The aim of these laboratory tests is to determine the correlation between the ageing and the measured parameters however, in many cases, the direct interaction between main deterioration processes and the examined phenomenon is not still clearly recognized. In this paper, parallel measurements of laboratory aged low voltage cables are evaluated by regression analysis. 相似文献
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为适应智能电能表自动化检定的要求,设计了由图像处理技术完成外观检测功能的系统,实现了外观检查的自动化,解决了人工检测方法工作量大、效果不佳的问题。系统采用高性能CCD相机完成图像采集,确保图像信息丰富完整。利用图像平滑去噪、形态学处理等技术完成图像的预处理,大幅降低后续比对的难度。运用基于高斯金字塔的混合配准算法完成图像配准,最终实现待检图像与模板图像之间匹配程度的检测。该方法检测时间短,正确率高,已成功应用于省级计量中心电能表自动化检定线,满足生产需求。 相似文献
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运载火箭多表冗余捷联惯组的故障诊断与决策 总被引:1,自引:0,他引:1
为了提高运载火箭惯导系统的可靠性,介绍了一种多表冗余捷联惯性测量组合的故障诊断和冗余信息重构技术,对陀螺仪和加速度计信息采取三取二的冗余、诊断的管理策略,将故障定位到具体惯组的某个敏感轴,对故障惯组隔离后进行信息重构,实现故障情况下的导航信息的正常输出,增强了运载火箭对惯组故障的适应能力。 相似文献
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针对寿命服从指数分布的随机截尾样本,研究单元及系统可靠度的评估方法,给出了系统可靠度置信下限估计方法,该方法同样适用于工程中常见的定时截尾样本与定数截尾样本的系统可靠度评估问题。首先通过分位数填充算法将随机截尾数据补充成虚拟完全样本,然后基于信仰推断,给出系统内每个单元失效率的信仰分布,最后根据指数分布的特点,从失效率角度出发,采用蒙特卡罗法对单元失效率进行随机抽样,结合系统可靠性模型得到系统失效率的分布,在给定置信水平下即可得到系统失效率上限,进而得到工程上特别关注的系统可靠度置信下限。 相似文献
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Richard L. Neitzel Maire S.A. Heikkinen Christopher C. Williams Susan Marie Viet Michael Dellarco 《Applied Acoustics》2016
Knowledge of the auditory and non-auditory effects of noise has increased dramatically over the past decade, but indoor noise exposure measurement methods have not advanced appreciably, despite the introduction of applicable new technologies. This study evaluated various conventional and smart devices for exposure assessment in the National Children’s Study. Three devices were tested: a sound level meter (SLM), a dosimeter, and a smart device with a noise measurement application installed. Instrument performance was evaluated in a series of semi-controlled tests in office environments over 96-h periods, followed by measurements made continuously in two rooms (a child’s bedroom and a most used room) in nine participating homes over a 7-day period with subsequent computation of a range of noise metrics. The SLMs and dosimeters yielded similar A-weighted average noise levels. Levels measured by the smart devices often differed substantially (showing both positive and negative bias, depending on the metric) from those measured via SLM and dosimeter, and demonstrated attenuation in some frequency bands in spectral analysis compared to SLM results. Virtually all measurements exceeded the Environmental Protection Agency’s 45 dBA day–night limit for indoor residential exposures. The measurement protocol developed here can be employed in homes, demonstrates the possibility of measuring long-term noise exposures in homes with technologies beyond traditional SLMs, and highlights potential pitfalls associated with measurements made by smart devices. 相似文献
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Smart cities are a rapidly growing IoT application. These smart cities mainly rely on wireless sensors to connect their different components (smart devices) together. Smart cities rely on the integration of IoT and 5G technologies, and this has created a demand for a massive IoT network of connected devices. The data traffic coming from indoor wireless networks (e.g., smart homes, smart hospitals, smart factories , or smart school buildings) contributes to over 80% of the total data traffic of the current IoT network. As smart cities and their applications grow, security and privacy challenges have become a major concern for billions of IoT smart devices. One reason for this could be the oversight of handling security issues of IoT devices by their manufacturers, which enables attackers to exploit the vulnerabilities in these devices by performing different types of attacks, e.g., DDoS and injection attacks. Intrusion detection is one way to detect and mitigate the risk of such attacks. In this paper, an intrusion detection method was proposed to detect injection attacks in IoT applications (e.g. smart cities). In this method, two types of feature selection techniques (constant removal and recursive feature elimination) were used and tested by a number of machine learning classifiers (i.e., SVM, Random Forest, and Decision Tree). The T-Test was conducted to evaluate the quality of this proposed feature selection method. Using the public dataset, AWID, the evaluation results showed that the decision tree classifier can be used to detect injection attacks with an accuracy of 99% using only 8 features, which were selected using the proposed feature selection method. Also, the comparison with the most related work showed the advantages of the proposed intrusion detection method. 相似文献