耐波性试验和试验的航行长度和统计误差估计

R. D. Pierce
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引用次数: 2

摘要

海道和由此产生的模型或全尺寸船的响应是随机过程。最终结果的准确性在很大程度上取决于测试运行的时间长短。因此,在耐浪性测试或试验的计划、执行和评估阶段,必须考虑运行长度及其对数据准确性的影响。存在两个基本问题领域:1。在测试或试验之前对运行长度进行估计,以便有效地执行任务,并将数据收集到所需的精度。2. 对过去采集的数据进行误差估计,以确定达到何种精度水平。运行长度直接影响处理结果的准确性或置信度。反过来,这种精度水平是任务优先级和输入介质(本例中为航道)的统计可变性之间的权衡。更高优先级的任务将要求更高的数据精度和更长的运行长度,而不断变化的海况将限制这种精度。实际上,所有特派团都必须考虑项目1和项目2,以协助执行任务前的规划,并更好地了解从前一个特派团收集的数据的可靠性。本文提出并描述了以下方法:确定估计给定数据样本的运行长度和统计误差所需的自动频谱有效峰值频率和半功率带宽。2. 估计随机过程均值、标准差、方差、自动谱和响应幅度算子(RAO)。估计与随机过程的均值、标准差、方差、自动谱和RAO相关的统计误差和运行长度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Run Length and Statistical Error Estimation for Seakeeping Tests and Trials
A seaway and the resulting responses of models or full-scale craft are random processes. The accuracy of the final results depends heavily on the length of the test runs. Therefore in the planning, execution, and evaluation phases of a seakeeping test or trial, run length and its effect on the accuracy of the data must be accounted for. Two basic problem areas exist: 1. Run length estimation prior to a test or trial so that the mission can be carried out efficiently, and data gathered to a desired accuracy. 2. Error estimation for data taken in the past to determine what accuracy level was reached. The run length directly affects the level of accuracy or confidence in the processed results. This accuracy level is, in turn, a trade-off between the task priority and the statistical variability of the input medium (the seaway in this case) A higher priority mission will call for a higher data accuracy and longer run length while a changing sea condition will put constraints on this accuracy. In effect, items 1 and 2 must be considered in all missions to aid in pre-mission planning and to better understand the reliability of data gathered from a previous mission. This paper presents and describes methods to: 1. Determine the auto spectrum effective peak frequencies and half-power bandwidths needed to estimate run length and statistical error for given data samples. 2. Estimate random process mean values, standard deviations, variance, auto spectra and Response Amplitude Operators (RAO' s). 3. Estimate the statistical errors and run lengths associated with the mean value, standard deviation, variance, auto spectra and RAO's of a random process.
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