Rare-earth based frustrated magnets have attracted great attention as excellent candidates for magnetic refrigeration at sub-Kelvin temperatures,while the experimental identification of systems exhibiting both large v...Rare-earth based frustrated magnets have attracted great attention as excellent candidates for magnetic refrigeration at sub-Kelvin temperatures,while the experimental identification of systems exhibiting both large volumetric cooling capacity and reduced working temperatures far below 1K remains a challenge.Here,through ultra-low temperature magnetism and thermodynamic characterizations,we unveil the large magnetocaloric effect(MCE)realized at sub-Kelvin temperatures in the frustrated Kagome antiferromagnet Gd_(3)BWO_(9)with T_(N)∼1.0 K.The isothermal magnetization curves indicate the existence of field(B)induced anisotropic magnetic phase diagrams,where four distinct magnetic phases for B‖c-axis and five magnetic phases for B‖ab-plane are identified at T<T_(N).The analysis of magnetic entropy S(B,T)data and direct adiabatic demagnetization tests reveal remarkable cooling performance at sub-Kelvin temperatures featured by a large volumetric entropy density of 502.2 mJ/K/cm^(3)and a low attainable minimal temperature T_(min)∼168mK from the initial cooling condition of 2K and 6 T,surpassing most Gd-based refrigerants previously documented in temperature ranges of 0.25–4 K.The realized T_(min)∼168mK far below T_(N)∼1.0K in Gd_(3)BWO_(9)is related to the combined effects of magnetic frustration and criticality-enhanced MCE,which together leave substantial magnetic entropy at reduced temperatures by enhancing spin fluctuations.展开更多
针对铣刀磨损状态监测中信号噪声大、监测效率低等问题,提出了一种基于能量权重法的变分模态分解(VMD)与黑寡妇(BWO)-支持向量机(SVM)的铣刀磨损状态监测方法。首先,运用VMD将铣削时产生的振动信号分解成若干固有模态函数(IMF)分量,并...针对铣刀磨损状态监测中信号噪声大、监测效率低等问题,提出了一种基于能量权重法的变分模态分解(VMD)与黑寡妇(BWO)-支持向量机(SVM)的铣刀磨损状态监测方法。首先,运用VMD将铣削时产生的振动信号分解成若干固有模态函数(IMF)分量,并通过能量加权合成峭度指标自适应提取出了包含磨损状态特征的IMF分量,并进行了信号重构,对重构信号进行了特征提取;然后,利用BWO算法优化SVM的参数,构建了BWO-SVM铣刀磨损状态监测模型;最后,为了验证上述方法的有效性,以某公司真实加工现场的PHM Society 2010铣刀全寿命周期的振动数据进行了实验,并且又通过实际的工程案例对此进行了验证。研究结果表明:通过所提方法自适应提取有效分量并进行信号重构后,降噪效果明显,并通过与遗传算法(GA)和粒子群算法(PSO)优化的SVM相比,经过BWO优化的SVM的训练时间缩短至25.142 s,同时监测精度达到97.246%;采用该方法对铣刀磨损状态进行监测,能够获得更快的识别速度与更高的准确性,提高了铣刀磨损状态监测的效率。展开更多
为克服传统白鲸优化算法(Beluga Whale Optimization,BWO)在3-5-3多项式插值机械臂轨迹优化中存在的路径长、时间耗费高及易陷入局部最优的问题,本文提出了一种增强型白鲸-蝠鲼融合优化算法(Enhanced Beluga Whale and manta ray fusion...为克服传统白鲸优化算法(Beluga Whale Optimization,BWO)在3-5-3多项式插值机械臂轨迹优化中存在的路径长、时间耗费高及易陷入局部最优的问题,本文提出了一种增强型白鲸-蝠鲼融合优化算法(Enhanced Beluga Whale and manta ray fusion Optimization algorithm,EBWO).该算法以机械臂最优运动时间为目标,构建约束优化模型,并通过增广拉格朗日乘子法转化为无约束形式.首先,利用改进的对数非线性Halton混沌序列优化种群初始化,提高搜索多样性与质量;其次,设计多方向正余弦白鲸位置更新机制,增强开发阶段搜索能力;再次,在中期迭代阶段引入改进的蝠鲼旋风链式觅食策略,并结合Levy飞行机制构建新觅食因子,以强化局部开发与全局跳跃能力;最后,提出基于资源竞争耦合机制的自适应鲸落策略,并引入量子隧穿效应,以提升算法跳出局部最优的能力与收敛速度.实验结果表明:在3-5-3轨迹优化中,EBWO较于传统BWO将时间优化效果提升了8.69%,并且与未优化的轨迹相比,优化后的时间缩短了42.13%.这一结果验证了其在复杂优化任务时的有效性与实用性.展开更多
开展电网计量装置电力互感器浸水后劣化特性的研究,对电网公司在洪涝灾害后电力互感器的风险评估与检修决策至关重要。为此,提出了基于健康指数与威布尔故障率模型的电力互感器浸水后劣化寿命预测方法,即通过采用模糊综合评价方法求解...开展电网计量装置电力互感器浸水后劣化特性的研究,对电网公司在洪涝灾害后电力互感器的风险评估与检修决策至关重要。为此,提出了基于健康指数与威布尔故障率模型的电力互感器浸水后劣化寿命预测方法,即通过采用模糊综合评价方法求解出互感器健康指数,用模糊语言描述互感器运行状态,利用改进的基于时间与设备状态的故障率模型确定当前状态下互感器故障率。进一步地,利用白鲸优化算法改进的最小二乘法(Beluga whale optimization-ordinary least squares,BWO-OLS)分段拟合出电力互感器威布尔故障率浴盆曲线,将它浸水后状态下的故障率映射到威布尔故障率浴盆曲线中,求解出电力互感器浸水后等效劣化寿命。选用8种不同型号电流互感器开展浸水实验,其测试结果表明:电流互感器浸水后会发生不可逆性的劣化,它们浸水后运行状态与模型评价结果一致,验证了浸水后劣化互感器寿命预测方法的有效性。展开更多
基金supported by the National Key Research and Development Program(Grant Nos.2024YFA1611200 and 2023YFA1406500)the National Natural Science Foundation of China(Grant Nos.12141002 and 52088101)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB1270000)。
文摘Rare-earth based frustrated magnets have attracted great attention as excellent candidates for magnetic refrigeration at sub-Kelvin temperatures,while the experimental identification of systems exhibiting both large volumetric cooling capacity and reduced working temperatures far below 1K remains a challenge.Here,through ultra-low temperature magnetism and thermodynamic characterizations,we unveil the large magnetocaloric effect(MCE)realized at sub-Kelvin temperatures in the frustrated Kagome antiferromagnet Gd_(3)BWO_(9)with T_(N)∼1.0 K.The isothermal magnetization curves indicate the existence of field(B)induced anisotropic magnetic phase diagrams,where four distinct magnetic phases for B‖c-axis and five magnetic phases for B‖ab-plane are identified at T<T_(N).The analysis of magnetic entropy S(B,T)data and direct adiabatic demagnetization tests reveal remarkable cooling performance at sub-Kelvin temperatures featured by a large volumetric entropy density of 502.2 mJ/K/cm^(3)and a low attainable minimal temperature T_(min)∼168mK from the initial cooling condition of 2K and 6 T,surpassing most Gd-based refrigerants previously documented in temperature ranges of 0.25–4 K.The realized T_(min)∼168mK far below T_(N)∼1.0K in Gd_(3)BWO_(9)is related to the combined effects of magnetic frustration and criticality-enhanced MCE,which together leave substantial magnetic entropy at reduced temperatures by enhancing spin fluctuations.
文摘针对铣刀磨损状态监测中信号噪声大、监测效率低等问题,提出了一种基于能量权重法的变分模态分解(VMD)与黑寡妇(BWO)-支持向量机(SVM)的铣刀磨损状态监测方法。首先,运用VMD将铣削时产生的振动信号分解成若干固有模态函数(IMF)分量,并通过能量加权合成峭度指标自适应提取出了包含磨损状态特征的IMF分量,并进行了信号重构,对重构信号进行了特征提取;然后,利用BWO算法优化SVM的参数,构建了BWO-SVM铣刀磨损状态监测模型;最后,为了验证上述方法的有效性,以某公司真实加工现场的PHM Society 2010铣刀全寿命周期的振动数据进行了实验,并且又通过实际的工程案例对此进行了验证。研究结果表明:通过所提方法自适应提取有效分量并进行信号重构后,降噪效果明显,并通过与遗传算法(GA)和粒子群算法(PSO)优化的SVM相比,经过BWO优化的SVM的训练时间缩短至25.142 s,同时监测精度达到97.246%;采用该方法对铣刀磨损状态进行监测,能够获得更快的识别速度与更高的准确性,提高了铣刀磨损状态监测的效率。
文摘开展电网计量装置电力互感器浸水后劣化特性的研究,对电网公司在洪涝灾害后电力互感器的风险评估与检修决策至关重要。为此,提出了基于健康指数与威布尔故障率模型的电力互感器浸水后劣化寿命预测方法,即通过采用模糊综合评价方法求解出互感器健康指数,用模糊语言描述互感器运行状态,利用改进的基于时间与设备状态的故障率模型确定当前状态下互感器故障率。进一步地,利用白鲸优化算法改进的最小二乘法(Beluga whale optimization-ordinary least squares,BWO-OLS)分段拟合出电力互感器威布尔故障率浴盆曲线,将它浸水后状态下的故障率映射到威布尔故障率浴盆曲线中,求解出电力互感器浸水后等效劣化寿命。选用8种不同型号电流互感器开展浸水实验,其测试结果表明:电流互感器浸水后会发生不可逆性的劣化,它们浸水后运行状态与模型评价结果一致,验证了浸水后劣化互感器寿命预测方法的有效性。
