为有效识别和剔除风电机组实测数据中的异常数据,通过分析风电机组实测数据的高维特征,提出一种基于流形学习的异常数据识别算法。首先,采用k-近邻互信息算法实现风电机组特征变量选择;随后,使用将样本间距离度量替换为欧几里得度量和...为有效识别和剔除风电机组实测数据中的异常数据,通过分析风电机组实测数据的高维特征,提出一种基于流形学习的异常数据识别算法。首先,采用k-近邻互信息算法实现风电机组特征变量选择;随后,使用将样本间距离度量替换为欧几里得度量和局部主成分分析(local principal component analysis,LPCA)差别加权和的优化t-分布随机近邻嵌入(t-distributed stochastic neighbor embedding,t-SNE)算法挖掘出高维流形数据中具有内在规律的低维特征,使得具有不同分布特征的数据在可视化二维空间中显著分离;最后,采用基于密度的噪声空间聚类(density-based spatial clustering of applications with noise,DBSCAN)算法对二维空间中的数据进行聚类。结果表明,与主成分分析(principal component analysis,PCA)算法、局部线性嵌入(locally linear embedding,LLE)算法和原t-SNE算法相比,所提方法能够对各种复杂工况数据进行可视化分离聚类,并对异常数据进行识别和剔除。展开更多
[Objective]This study aims to investigate the multi-body hydrodynamic interaction mechanisms during offshore lifting operations of aquaculture net cages in wind-fishery integration systems.By integrating numerical sim...[Objective]This study aims to investigate the multi-body hydrodynamic interaction mechanisms during offshore lifting operations of aquaculture net cages in wind-fishery integration systems.By integrating numerical simulations and dynamic analysis methods,this study systematically investigates the coupled dynamic response characteristics during the cage-carrier vessel separation process to reveal its dynamic evolution patterns and key influence mechanisms.[Method]Based on potential flow theory,a fully coupled dynamic analysis model of crane vessel-net cage-semi-submersible barge was established for a marine ranch project in Guangdong.The complete lifting process was dynamically simulated using SESAM software.Five typical operating sea states were configured to investigate the influence of wave parameters on the system's motion response under combined wave-current-wind actions.[Result]The results demonstrate that wave period dominates the system stability.Under short-period conditions,the system maintains stable motion with relatively small horizontal relative displacements,while long-period conditions excite low-frequency resonance,leading to significant slow-drift motions.Vertical response analysis reveals that long-period waves cause severe relative displacement fluctuations between the cage and semi-submersible vessel,with actual displacement amplitudes doubling the preset safety target of 2.045 m.Quantitative analysis further indicates that when significant wave height increases from 1.0 m to 1.5 m,the actual displacement amplitude increases by approximately 20%relative to the target displacement of 2.045 m,demonstrating that its influence is significantly weaker than the displacement variations induced by wave period changes.The complete dynamic simulation successfully captures the continuous dynamic response characteristics during the lifting process.[Conclusion]This research clarifies the influence mechanisms of wave parameters on the cage lifting process,identifying wave period as the crucial factor for operational safety.An operation window assessment method incorporating multi-body coupling effects is established,proposing a safety criterion with peak period not exceeding six seconds as the core requirement.The findings provide theoretical foundation for safe installation of marine ranch net cages and offer valuable references for similar offshore lifting operations.展开更多
文摘为有效识别和剔除风电机组实测数据中的异常数据,通过分析风电机组实测数据的高维特征,提出一种基于流形学习的异常数据识别算法。首先,采用k-近邻互信息算法实现风电机组特征变量选择;随后,使用将样本间距离度量替换为欧几里得度量和局部主成分分析(local principal component analysis,LPCA)差别加权和的优化t-分布随机近邻嵌入(t-distributed stochastic neighbor embedding,t-SNE)算法挖掘出高维流形数据中具有内在规律的低维特征,使得具有不同分布特征的数据在可视化二维空间中显著分离;最后,采用基于密度的噪声空间聚类(density-based spatial clustering of applications with noise,DBSCAN)算法对二维空间中的数据进行聚类。结果表明,与主成分分析(principal component analysis,PCA)算法、局部线性嵌入(locally linear embedding,LLE)算法和原t-SNE算法相比,所提方法能够对各种复杂工况数据进行可视化分离聚类,并对异常数据进行识别和剔除。
文摘[Objective]This study aims to investigate the multi-body hydrodynamic interaction mechanisms during offshore lifting operations of aquaculture net cages in wind-fishery integration systems.By integrating numerical simulations and dynamic analysis methods,this study systematically investigates the coupled dynamic response characteristics during the cage-carrier vessel separation process to reveal its dynamic evolution patterns and key influence mechanisms.[Method]Based on potential flow theory,a fully coupled dynamic analysis model of crane vessel-net cage-semi-submersible barge was established for a marine ranch project in Guangdong.The complete lifting process was dynamically simulated using SESAM software.Five typical operating sea states were configured to investigate the influence of wave parameters on the system's motion response under combined wave-current-wind actions.[Result]The results demonstrate that wave period dominates the system stability.Under short-period conditions,the system maintains stable motion with relatively small horizontal relative displacements,while long-period conditions excite low-frequency resonance,leading to significant slow-drift motions.Vertical response analysis reveals that long-period waves cause severe relative displacement fluctuations between the cage and semi-submersible vessel,with actual displacement amplitudes doubling the preset safety target of 2.045 m.Quantitative analysis further indicates that when significant wave height increases from 1.0 m to 1.5 m,the actual displacement amplitude increases by approximately 20%relative to the target displacement of 2.045 m,demonstrating that its influence is significantly weaker than the displacement variations induced by wave period changes.The complete dynamic simulation successfully captures the continuous dynamic response characteristics during the lifting process.[Conclusion]This research clarifies the influence mechanisms of wave parameters on the cage lifting process,identifying wave period as the crucial factor for operational safety.An operation window assessment method incorporating multi-body coupling effects is established,proposing a safety criterion with peak period not exceeding six seconds as the core requirement.The findings provide theoretical foundation for safe installation of marine ranch net cages and offer valuable references for similar offshore lifting operations.
