以内燃机典型摩擦副缸套-活塞系统为研究对象,设计和搭建内燃机缸套-活塞系统状态监测试验台。针对传统最大熵方法分析润滑油中磨粒监测数据存在的缺点,提出改进的分数矩最大熵方法(Fractional Moment Maximum Entropy Method, FM-MEM)...以内燃机典型摩擦副缸套-活塞系统为研究对象,设计和搭建内燃机缸套-活塞系统状态监测试验台。针对传统最大熵方法分析润滑油中磨粒监测数据存在的缺点,提出改进的分数矩最大熵方法(Fractional Moment Maximum Entropy Method, FM-MEM),并结合食肉植物优化算法(Carnivorous Plant Algorithm, CPA)对关键参数进行寻优求解。对润滑油中磨粒监测数据进行阈值划分,实现内燃机健康状态评估,然后将理论与试验相结合,以在线磨粒监测为主,从润滑油磨粒、理化指标以及表面形貌3个方面对内燃机缸套-活塞系统的运行状态进行监测,分析低速工况下缸套-活塞系统各个时间段的磨损健康状态及磨粒含量变化趋势,通过内燃机整机的在线磨粒监测试验,证明该方法可实现对内燃机缸套-活塞系统的实时状态监测。展开更多
在平抑光伏功率波动过程中,电池储能系统(battery energy storage system,BESS)因保持持续充、放电状态而导致寿命损耗较大。基于电池分组控制技术,提出考虑寿命延长的BESS平抑光伏分组功率分配办法。设计了食肉植物算法优化的改进雨流...在平抑光伏功率波动过程中,电池储能系统(battery energy storage system,BESS)因保持持续充、放电状态而导致寿命损耗较大。基于电池分组控制技术,提出考虑寿命延长的BESS平抑光伏分组功率分配办法。设计了食肉植物算法优化的改进雨流计数法,以获取光伏并网功率指令;利用小波包分解确定电池组数量及容量,同时根据设计的充、放电原则形成电池组的功率调节指令;进行电池组组别重置时,将BESS中诸多电池单元进行有序分配;提出二次功率分配策略,获取各电池单元的功率调节指令,二次分配时还应用了重复补发原则以最大限度跟踪功率调节指令,并保证组内电池单元荷电状态均衡。对所提功率分配方法进行了仿真验证,并与其他5种策略进行了对比,结果表明,所提功率分配方法实现了BESS对于功率调节指令的更好跟踪,降低了光伏并网功率波动率,延长了电池单元的使用寿命。展开更多
Big data analysis is confronted with the obstacle of high dimensionality in data samples.To address this issue,researchers have devised a multitude of intel-ligent optimization algorithms aimed at enhancing big data a...Big data analysis is confronted with the obstacle of high dimensionality in data samples.To address this issue,researchers have devised a multitude of intel-ligent optimization algorithms aimed at enhancing big data analysis techniques.Among these algorithms is the War Strategy Optimization(WSO)proposed in 2022,which distinguishes itself from other intelligence algorithms through its potent optimization capabilities.Nevertheless,the WSO exhibits limitations in its global search capacity and is susceptible to becoming trapped in local optima when dealing with high-dimensional problems.To surmount these shortcomings and improve the performance of WSO in handling the challenges posed by high dimensionality in big data,this paper introduces an enhanced version of the WSO based on the carnivorous plant algorithm(CPA)and shared niche.The grouping concept and update strategy of CPA are incorporated into WSO,and its update strategy is modified through the introduction of a shared small habitat approach combined with an elite strategy to create a novel improved algorithm.Simula-tion experiments were conducted to compare this new War Strategy Optimization(CSWSO)with WSO,RKWSO,I-GWO,NCHHO and FDB-SDO using 16 test functions.Experimental results demonstrate that the proposed enhanced algorithm exhibits superior optimization accuracy and stability,providing a novel approach to addressing the challenges posed by high dimensionality in big data.展开更多
文摘以内燃机典型摩擦副缸套-活塞系统为研究对象,设计和搭建内燃机缸套-活塞系统状态监测试验台。针对传统最大熵方法分析润滑油中磨粒监测数据存在的缺点,提出改进的分数矩最大熵方法(Fractional Moment Maximum Entropy Method, FM-MEM),并结合食肉植物优化算法(Carnivorous Plant Algorithm, CPA)对关键参数进行寻优求解。对润滑油中磨粒监测数据进行阈值划分,实现内燃机健康状态评估,然后将理论与试验相结合,以在线磨粒监测为主,从润滑油磨粒、理化指标以及表面形貌3个方面对内燃机缸套-活塞系统的运行状态进行监测,分析低速工况下缸套-活塞系统各个时间段的磨损健康状态及磨粒含量变化趋势,通过内燃机整机的在线磨粒监测试验,证明该方法可实现对内燃机缸套-活塞系统的实时状态监测。
文摘在平抑光伏功率波动过程中,电池储能系统(battery energy storage system,BESS)因保持持续充、放电状态而导致寿命损耗较大。基于电池分组控制技术,提出考虑寿命延长的BESS平抑光伏分组功率分配办法。设计了食肉植物算法优化的改进雨流计数法,以获取光伏并网功率指令;利用小波包分解确定电池组数量及容量,同时根据设计的充、放电原则形成电池组的功率调节指令;进行电池组组别重置时,将BESS中诸多电池单元进行有序分配;提出二次功率分配策略,获取各电池单元的功率调节指令,二次分配时还应用了重复补发原则以最大限度跟踪功率调节指令,并保证组内电池单元荷电状态均衡。对所提功率分配方法进行了仿真验证,并与其他5种策略进行了对比,结果表明,所提功率分配方法实现了BESS对于功率调节指令的更好跟踪,降低了光伏并网功率波动率,延长了电池单元的使用寿命。
文摘Big data analysis is confronted with the obstacle of high dimensionality in data samples.To address this issue,researchers have devised a multitude of intel-ligent optimization algorithms aimed at enhancing big data analysis techniques.Among these algorithms is the War Strategy Optimization(WSO)proposed in 2022,which distinguishes itself from other intelligence algorithms through its potent optimization capabilities.Nevertheless,the WSO exhibits limitations in its global search capacity and is susceptible to becoming trapped in local optima when dealing with high-dimensional problems.To surmount these shortcomings and improve the performance of WSO in handling the challenges posed by high dimensionality in big data,this paper introduces an enhanced version of the WSO based on the carnivorous plant algorithm(CPA)and shared niche.The grouping concept and update strategy of CPA are incorporated into WSO,and its update strategy is modified through the introduction of a shared small habitat approach combined with an elite strategy to create a novel improved algorithm.Simula-tion experiments were conducted to compare this new War Strategy Optimization(CSWSO)with WSO,RKWSO,I-GWO,NCHHO and FDB-SDO using 16 test functions.Experimental results demonstrate that the proposed enhanced algorithm exhibits superior optimization accuracy and stability,providing a novel approach to addressing the challenges posed by high dimensionality in big data.
