近日,明阳智能欧洲公司(Ming Yang Europe)正式宣布加入德国联邦海上风能协会(Bundesverband Windenergie Offshore,简称BWO)。作为德国乃至欧洲海上风电领域最具影响力的行业组织,BWO的接纳标志着明阳智能在欧洲市场的本土化战略迈出...近日,明阳智能欧洲公司(Ming Yang Europe)正式宣布加入德国联邦海上风能协会(Bundesverband Windenergie Offshore,简称BWO)。作为德国乃至欧洲海上风电领域最具影响力的行业组织,BWO的接纳标志着明阳智能在欧洲市场的本土化战略迈出了坚实的一步,同时也向业界释放了其深耕欧洲、共建生态的强烈信号。展开更多
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
文摘近日,明阳智能欧洲公司(Ming Yang Europe)正式宣布加入德国联邦海上风能协会(Bundesverband Windenergie Offshore,简称BWO)。作为德国乃至欧洲海上风电领域最具影响力的行业组织,BWO的接纳标志着明阳智能在欧洲市场的本土化战略迈出了坚实的一步,同时也向业界释放了其深耕欧洲、共建生态的强烈信号。
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。
