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基于特征适应度分析的剩余寿命预测方法及应用 被引量:1
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作者 陈长骏 王凌 +3 位作者 钱霖泽 褚永华 王志康 张鞠成 《控制工程》 CSCD 北大核心 2021年第7期1483-1489,共7页
针对地铁车辆客室电动塞拉门传动装置润滑不良的问题,提出了一种基于特征适应度分析的剩余寿命预测方法。该方法首先采集电机工作电流提取各时域特征,分析各劣化特征间的关联性,得到特征关联矩阵及相对关联权重,然后利用劣化评价指标分... 针对地铁车辆客室电动塞拉门传动装置润滑不良的问题,提出了一种基于特征适应度分析的剩余寿命预测方法。该方法首先采集电机工作电流提取各时域特征,分析各劣化特征间的关联性,得到特征关联矩阵及相对关联权重,然后利用劣化评价指标分析各特征自身劣化过程的固有特性,通过构建特征混合适应度函数筛选最优劣化特征子集。最后,根据润滑不良故障的退化特性建立劣化模型,利用最优特征的历史数据初始化模型参数,结合粒子滤波算法递推更新模型参数实现后续剩余使用寿命在线预测。实验结果表明,在电动塞拉门丝杆润滑不良故障的剩余寿命预测中,该方法选取的最优特征较其他特征具有更好的预测精度及鲁棒性。 展开更多
关键词 电动塞拉门 润滑不良 剩余使用寿命预测 特征适应度分析 粒子滤波
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基于自适应特征选择与KNN的网络流量分类研究 被引量:1
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作者 李道全 李腾 李玉秀 《计算机工程与应用》 CSCD 北大核心 2023年第12期270-277,共8页
随着互联网技术的不断发展,用户可以在手机或电脑上通过各种应用程序访问互联网,但一些恶意程序产生的异常流量给网络环境带来了危害。针对这一问题,提出了一种基于自适应特征选择与改进KNN的网络流量分类模型。通过引进余弦相似度的互... 随着互联网技术的不断发展,用户可以在手机或电脑上通过各种应用程序访问互联网,但一些恶意程序产生的异常流量给网络环境带来了危害。针对这一问题,提出了一种基于自适应特征选择与改进KNN的网络流量分类模型。通过引进余弦相似度的互信息法设置了特征筛选倾向度对数据集所有特征进行排序,根据每个特征子集的特征适应度选出最优特征子集,根据各类流量之间的类间距离拆解多分类问题,采用改进KNN算法对流量进行分类。实验结果表明,所提方法在样本不均衡的相似类型流量分类问题上提升效果显著,且整体达到了较好的分类性能。 展开更多
关键词 流量分类 K近邻法 特征适应度 类间距离
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ROBUST ACOUSTIC SOURCE LOCALIZATION FOR DIGITAL HEARING AIDS IN NOISE AND REVERBERANT ENVIRONMENT 被引量:1
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作者 赵立业 李宏生 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2010年第2期176-182,共7页
A new method in digital hearing aids to adaptively localize the speech source in noise and reverberant environment is proposed. Based on the room reverberant model and the multichannel adaptive eigenvalue decompositi... A new method in digital hearing aids to adaptively localize the speech source in noise and reverberant environment is proposed. Based on the room reverberant model and the multichannel adaptive eigenvalue decomposition (MCAED) algorithm, the proposed method can iteratively estimate impulse response coefficients between the speech source and microphones by the adaptive subgradient projection method. Then, it acquires the time delays of microphone pairs, and calculates the source position by the geometric method. Compared with the traditional normal least mean square (NLMS) algorithm, the adaptive subgradient projection method achieves faster and more accurate convergence in a low signal-to-noise ratio (SNR) environment. Simulations for glasses digital hearing aids with four-component square array demonstrate the robust performance of the proposed method. 展开更多
关键词 hearing aids acoustic source localization multichannel adaptive eigenvalue decomposition (MCAED) algorithms adaptive subgradient projection method
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Radar emitter signal recognition based on multi-scale wavelet entropy and feature weighting 被引量:16
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作者 李一兵 葛娟 +1 位作者 林云 叶方 《Journal of Central South University》 SCIE EI CAS 2014年第11期4254-4260,共7页
In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on m... In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on multi-scale wavelet entropy feature extraction and feature weighting was proposed. With the only priori knowledge of signal to noise ratio(SNR), the method of extracting multi-scale wavelet entropy features of wavelet coefficients from different received signals were combined with calculating uneven weight factor and stability weight factor of the extracted multi-dimensional characteristics. Radar emitter signals of different modulation types and different parameters modulated were recognized through feature weighting and feature fusion. Theoretical analysis and simulation results show that the presented algorithm has a high recognition rate. Additionally, when the SNR is greater than-4 d B, the correct recognition rate is higher than 93%. Hence, the proposed algorithm has great application value. 展开更多
关键词 emitter recognition multi-scale wavelet entropy feature weighting uneven weight factor stability weight factor
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Feature extraction of gear-localized defect using adaptive lifting scheme and local gradient maps
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作者 Zhang Lu Zhao Hong +3 位作者 Li Zhen Qi Keyu Li Zongyao Yao Nianling 《Engineering Sciences》 EI 2013年第1期78-82,88,共6页
In this paper,the adaptive lifting scheme (ALS) and local gradient maps (LGM) are proposed to isolate the transient feature components from the gearbox vibration signals. Based on entropy minimization rule,the ALS is ... In this paper,the adaptive lifting scheme (ALS) and local gradient maps (LGM) are proposed to isolate the transient feature components from the gearbox vibration signals. Based on entropy minimization rule,the ALS is employed to change properties of an initial wavelet and design adaptive wavelet. Then LGM is applied to characterize the transient feature components in detail signal of decomposition results using ALS. In the present studies, the orthogonal Daubechies 4 (Db 4) wavelet is used as the initial wavelet. The proposed method is applied to both simulated signals and vibration signals acquired from a gearbox for periodic impulses detection. The two conventional methods (cepstrum analysis and Hilbert envelope analysis) and the orthogonal Db4 wavelet are also used to analyze the same signals for comparison. The results demonstrate that the proposed method is more effective in extracting transient components from noisy signals. 展开更多
关键词 adaptive lifting scheme local gradient maps GEARBOX fault detection
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