为了解决滚动轴承振动信号中微弱故障信息难以提取的问题,提出了一种基于奇异值分解(Singular Value Decomposition,SVD)和Teager-Kaiser能量算子(Teager-Kaiser Energy Operator,TKEO)的轴承振动信号特征提取方法。采用SVD将突变信息...为了解决滚动轴承振动信号中微弱故障信息难以提取的问题,提出了一种基于奇异值分解(Singular Value Decomposition,SVD)和Teager-Kaiser能量算子(Teager-Kaiser Energy Operator,TKEO)的轴承振动信号特征提取方法。采用SVD将突变信息从背景噪声和光滑信号中分离,提取信号的突变信息;利用TKEO计算突变信息的瞬时能量,对该能量信号进行频谱分析,从而提取出轴承振动信号的能量频谱特征,用于故障检测。将该方法应用于轴承外圈、内圈局部故障状态下的振动信号特征提取,利用特征信息能够准确检测并识别出故障类型,表明了该方法的可行性和有效性。展开更多
针对时变负载下,笼型电机定子电流呈现出非平稳、非周期性,使得现有时变负载下的转子断条故障识别方法受电流基频调制影响而出现诊断失效的问题,提出了一种基于提格-凯撒能量算子(Teager-Kaiser energy operator,TKEO)的时变负载下笼型...针对时变负载下,笼型电机定子电流呈现出非平稳、非周期性,使得现有时变负载下的转子断条故障识别方法受电流基频调制影响而出现诊断失效的问题,提出了一种基于提格-凯撒能量算子(Teager-Kaiser energy operator,TKEO)的时变负载下笼型电机转子断条故障诊断方法。该方法采用TKEO提取电流信号的瞬时频率,以判断电机断条故障的严重程度。为验证该方法的有效性和优越性,通过实验获取不同健康状态和不同负载条件下的电流信号,并对其进行诊断。同时将分析结果与传统方法进行了多维度的比较。结果表明:该方法在时变负载下能够更准确地区分电机的健康状态,对负载扰动具有更强的鲁棒性,特别是轻载运行状态下,该方法的相对变化梯度数值差异相较于传统方法高4~6倍,此外,提取到的故障频率波动范围更集中在0~5 Hz之间。展开更多
Fault detection and classification is a key challenge for the protection of High Voltage DC(HVDC)transmission lines.In this paper,the Teager-Kaiser Energy Operator(TKEO)algorithm associated with a decision tree-based ...Fault detection and classification is a key challenge for the protection of High Voltage DC(HVDC)transmission lines.In this paper,the Teager-Kaiser Energy Operator(TKEO)algorithm associated with a decision tree-based fault classi-fier is proposed to detect and classify various DC faults.The Change Identification Filter is applied to the average and differential current components,to detect the first instant of fault occurrence(above threshold)and register a Change Identified Point(CIP).Further,if a CIP is registered for a positive or negative line,only three samples of currents(i.e.,CIP and each side of CIP)are sent to the proposed TKEO algorithm,which produces their respective 8 indices through which the,fault can be detected along with its classification.The new approach enables quicker detection allowing utility grids to be restored as soon as possible.This novel approach also reduces computing complexity and the time required to identify faults with classification.The importance and accuracy of the proposed scheme are also thor-oughly tested and compared with other methods for various faults on HVDC transmission lines.展开更多
文摘为了解决滚动轴承振动信号中微弱故障信息难以提取的问题,提出了一种基于奇异值分解(Singular Value Decomposition,SVD)和Teager-Kaiser能量算子(Teager-Kaiser Energy Operator,TKEO)的轴承振动信号特征提取方法。采用SVD将突变信息从背景噪声和光滑信号中分离,提取信号的突变信息;利用TKEO计算突变信息的瞬时能量,对该能量信号进行频谱分析,从而提取出轴承振动信号的能量频谱特征,用于故障检测。将该方法应用于轴承外圈、内圈局部故障状态下的振动信号特征提取,利用特征信息能够准确检测并识别出故障类型,表明了该方法的可行性和有效性。
文摘针对时变负载下,笼型电机定子电流呈现出非平稳、非周期性,使得现有时变负载下的转子断条故障识别方法受电流基频调制影响而出现诊断失效的问题,提出了一种基于提格-凯撒能量算子(Teager-Kaiser energy operator,TKEO)的时变负载下笼型电机转子断条故障诊断方法。该方法采用TKEO提取电流信号的瞬时频率,以判断电机断条故障的严重程度。为验证该方法的有效性和优越性,通过实验获取不同健康状态和不同负载条件下的电流信号,并对其进行诊断。同时将分析结果与传统方法进行了多维度的比较。结果表明:该方法在时变负载下能够更准确地区分电机的健康状态,对负载扰动具有更强的鲁棒性,特别是轻载运行状态下,该方法的相对变化梯度数值差异相较于传统方法高4~6倍,此外,提取到的故障频率波动范围更集中在0~5 Hz之间。
文摘Fault detection and classification is a key challenge for the protection of High Voltage DC(HVDC)transmission lines.In this paper,the Teager-Kaiser Energy Operator(TKEO)algorithm associated with a decision tree-based fault classi-fier is proposed to detect and classify various DC faults.The Change Identification Filter is applied to the average and differential current components,to detect the first instant of fault occurrence(above threshold)and register a Change Identified Point(CIP).Further,if a CIP is registered for a positive or negative line,only three samples of currents(i.e.,CIP and each side of CIP)are sent to the proposed TKEO algorithm,which produces their respective 8 indices through which the,fault can be detected along with its classification.The new approach enables quicker detection allowing utility grids to be restored as soon as possible.This novel approach also reduces computing complexity and the time required to identify faults with classification.The importance and accuracy of the proposed scheme are also thor-oughly tested and compared with other methods for various faults on HVDC transmission lines.