Abstract In vibration-based structural health monitoring (SHM), if the data are collected at a higher sampling rate from sensors, a large amount of computing resources and space resources will be consumed. For offshore platforms with limited space resources, there are many difficulties in long-term continuous monitoring. Aiming at this problem, the influence of sampling rate on structural damage identification is studied by comparing and analyzing the acceleration and posture sensors commonly used in offshore platform monitoring. In the simulation of parameter change of nonlinear system, random decrements and their spectrum characteristics are extracted from acceleration and displacement data respectively under different sampling rates, and the characteristics are classified by support vector machine (SVM) to identify the rule of change. The research of model experiment data also shows that the low sampling rate data can realize the identification of the damage, and the recognition degree of the low sampling rate data based on posture is not lower than that of the acceleration. The method is applied to the monitoring data analysis of FPSO soft york single-point mooring system and the damage situation is identical with the actual situation. The results show that the structural damage can be reflected from the low sampling rate posture monitoring data.

中文翻译：

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基于振动的海洋平台shm传感器采样率选择研究

摘要 在基于振动的结构健康监测（SHM）中，如果以更高的采样率从传感器采集数据，将消耗大量的计算资源和空间资源。对于空间资源有限的海上平台，长期连续监测存在诸多困难。针对这一问题，通过对比分析海上平台监测中常用的加速度和姿态传感器，研究采样率对结构损伤识别的影响。在非线性系统参数变化的模拟中，分别从加速度和位移数据中提取不同采样率下的随机减量及其谱特征，并通过支持向量机（SVM）对特征进行分类，识别变化规律。模型实验数据的研究也表明，低采样率数据可以实现损伤的识别，基于姿态的低采样率数据的识别度不低于加速度。将该方法应用于FPSO软约克单点系泊系统监测数据分析，破损情况与实际情况一致。结果表明，结构损伤可以从低采样率姿态监测数据中反映出来。将该方法应用于FPSO软约克单点系泊系统监测数据分析，破损情况与实际情况一致。结果表明，结构损伤可以从低采样率姿态监测数据中反映出来。将该方法应用于FPSO软约克单点系泊系统监测数据分析，破损情况与实际情况一致。结果表明，结构损伤可以从低采样率姿态监测数据中反映出来。