In the constant-stress accelerated life test, estimation issues are discussed for a generalized half-normal distribution under a log-linear life-stress model. The maximum likelihood estimates with the corresponding fi...In the constant-stress accelerated life test, estimation issues are discussed for a generalized half-normal distribution under a log-linear life-stress model. The maximum likelihood estimates with the corresponding fixed point type iterative algorithm for unknown parameters are presented, and the least square estimates of the parameters are also proposed. Meanwhile, confidence intervals of model parameters are constructed by using the asymptotic theory and bootstrap technique. Numerical illustration is given to investigate the performance of our methods.展开更多
为抑制白噪声和窄带干扰对局部放电脉冲信号能量测量的影响,提出了一种基于噪声参数的能量估计方法。研究了现场信号模型和信号能量谱系数的概率分布,得到噪声参数已知条件下脉冲信号能量的最大似然估计。同时为获得噪声参数,将采样数...为抑制白噪声和窄带干扰对局部放电脉冲信号能量测量的影响,提出了一种基于噪声参数的能量估计方法。研究了现场信号模型和信号能量谱系数的概率分布,得到噪声参数已知条件下脉冲信号能量的最大似然估计。同时为获得噪声参数,将采样数据划分成信号帧和噪声帧,采用3F–C法估计了白噪声和窄带干扰参数。通过仿真实验和实测数据处理,与传统小波包降噪方法的结果进行了对比。数据分析结果表明:无论是针对单一白噪声环境还是存在窄带干扰的混合噪声环境,该能量估计方法的准确性均优于传统小波包降噪方法,且随着信噪比的降低和信号时间窗口长度的增加,该方法表现出更明显的优势。在信噪比为–8 d B的条件下,使用该方法对实测局部放电脉冲信号进行能量估计的相对误差仅为4.07%,而使用小波包降噪方法时相对误差则达到44.12%。展开更多
基金supported by the National Natural Science Foundation of China(1150143371473187)the Natural Science Basic Research Plan in Shaanxi Province of China(2016JQ1014)
文摘In the constant-stress accelerated life test, estimation issues are discussed for a generalized half-normal distribution under a log-linear life-stress model. The maximum likelihood estimates with the corresponding fixed point type iterative algorithm for unknown parameters are presented, and the least square estimates of the parameters are also proposed. Meanwhile, confidence intervals of model parameters are constructed by using the asymptotic theory and bootstrap technique. Numerical illustration is given to investigate the performance of our methods.
文摘为抑制白噪声和窄带干扰对局部放电脉冲信号能量测量的影响,提出了一种基于噪声参数的能量估计方法。研究了现场信号模型和信号能量谱系数的概率分布,得到噪声参数已知条件下脉冲信号能量的最大似然估计。同时为获得噪声参数,将采样数据划分成信号帧和噪声帧,采用3F–C法估计了白噪声和窄带干扰参数。通过仿真实验和实测数据处理,与传统小波包降噪方法的结果进行了对比。数据分析结果表明:无论是针对单一白噪声环境还是存在窄带干扰的混合噪声环境,该能量估计方法的准确性均优于传统小波包降噪方法,且随着信噪比的降低和信号时间窗口长度的增加,该方法表现出更明显的优势。在信噪比为–8 d B的条件下,使用该方法对实测局部放电脉冲信号进行能量估计的相对误差仅为4.07%,而使用小波包降噪方法时相对误差则达到44.12%。
