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Parameter Estimation for Blur Image Combining Defocus and Motion Blur using Cepstrum Analysis 被引量:5
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作者 周曲 颜国正 王文兴 《Journal of Shanghai Jiaotong university(Science)》 EI 2007年第6期700-706,共7页
The degraded parameters recognition is very important for the restoration of blurred images. There are two common types of blurs for most camera systems. One is the defocus blur due to the optical system's defocus... The degraded parameters recognition is very important for the restoration of blurred images. There are two common types of blurs for most camera systems. One is the defocus blur due to the optical system's defocus phenomenon and the other is the motion blur due to the relative movement between the objectives and the camera. Compared with the recognition for the blurred image with only one blur model, the parameter estimation for the picture combining defocus and motion blur models is a more complicated mission. A method was proposed for computer to estimate the parameters of defocus blur and motion blur in cepstrum area simultaneously. According to characters of both blur models in the frequency domain, an adjustment approach was suggested in the frequency area and then convert to the cepstrum field to increase the accuracy of measurement. 展开更多
关键词 point SPREAD function (PSF) DEFOCUS motion BLUR cepstrum
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Extraction of Echo Characteristics of Underwater Target Based on Cepstrum Method 被引量:1
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作者 Hongjian Jia Xiukun Li +1 位作者 Xiangxia Meng Yang Yang 《Journal of Marine Science and Application》 CSCD 2017年第2期216-224,共9页
The analysis and characteristic extraction of target echo characteristics are important in underwater target detection and recognition. Rigid acoustic scattering components are generally used as major echo contributor... The analysis and characteristic extraction of target echo characteristics are important in underwater target detection and recognition. Rigid acoustic scattering components are generally used as major echo contributors with relatively stable characteristic information. Previous studies focus on echo characteristics from a single angle, thereby limiting the amount of extracted characteristic information. This paper aims to establish a full-angle rigid echo components model and overcome the difficulty of the extraction of time delay characteristics of narrow-band acoustic scattering echoes. On the basis of the analysis of the target echo highlight model, the echo characteristics of rigid acoustic scattering components are extracted in the cepstrum domain, and a wavelet process is proposed to enhance the effect of time delay estimation. Experimental data indicate that the extracted time delay characteristics accord with the rigid echo characteristics of underwater target, thereby validating the effectiveness of the cepstrum method. 展开更多
关键词 UNDERWATER target rigid scattering ECHOES time delay CHARACTERISTICS cepstrum wavelet enhancement ECHO characteristic
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Cepstrum analysis of seismic source characteristics
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作者 魏富胜 黎明 《Acta Seismologica Sinica(English Edition)》 CSCD 2003年第1期50-58,共9页
This paper introduces the concept of cepstrum. By investigating the difference in source characteristics between earthquakes and explosions the paper infers the manifestation of source difference in various variable d... This paper introduces the concept of cepstrum. By investigating the difference in source characteristics between earthquakes and explosions the paper infers the manifestation of source difference in various variable domains, and seeks for effective means to express such source difference. Extending the approach of source discrimination from time and frequency domain to the cepstrum domain, the paper proposes a method of cepstrum analysis for recognizing the characteristics of seismic sources and establishes criteria for identifying the type of seismic sources. Cepstrum analysis on some recent earthquakes and explosions has been made, and the result shows that the method is quite effective in practice. 展开更多
关键词 cepstrum seismic source DISCRIMINATION
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NEW AUTOREGRESSIVE MOVING AVERAGE SPECTRUM ESTIMATION AND CEPSTRUM ALGORITHM
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作者 Zhou Zhaojing,Cheng JieChina Institute of Metrology 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 1997年第2期125-129,共3页
Based on the deduction of the C parameter estimation, a new method to estimate C Parameters from the AR parameters of the ARMA model and auto-related function is proposed , The method reduces the computation complexit... Based on the deduction of the C parameter estimation, a new method to estimate C Parameters from the AR parameters of the ARMA model and auto-related function is proposed , The method reduces the computation complexity of the conventional interative algorithm in MA parameter estimation, thus make the algorithm of ARMA model spectral estimation simpler. On account of this method, a new algo- rithm of cepstrum analysis is put forward . Computer simulation indicates that the proposed cepstrum al- gorithm has the merits of few sidelobes and high resolution . And the algorithm is very useful to the ding- nosis of machinery failure . 展开更多
关键词 SPECTRUM ESTIMATION cepstrum RESOLUTION
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Simulating Study of Dynamic Load Spectra Identification Method of Machinery in Cepstrum Domain 被引量:9
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作者 HONG Cong-hua QIAO Shu-yun WU Miao 《Journal of China University of Mining and Technology》 EI 2006年第1期22-24,共3页
Based on the platform of Matlab and the theory of digital signal processing, we propose a method in the cepstrum domain for dynamic load spectra identification of machinery. We demonstrate that the dynamic load spectr... Based on the platform of Matlab and the theory of digital signal processing, we propose a method in the cepstrum domain for dynamic load spectra identification of machinery. We demonstrate that the dynamic load spectra can be identified from the response signal of the system, based on cepstra. An ARMA model is built based on the harmonic retrieval by high-order spectra. The coefficients of a Green function are determined and the window width can be estimated. Finally the effectiveness of the method is validated by simulation results. 展开更多
关键词 对数逆谱 光谱分析 数值模拟 动力负荷 机械
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Parameter recognition for defocus blur image using cepstrum analysis 被引量:1
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作者 周曲 《High Technology Letters》 EI CAS 2008年第3期276-281,共6页
Successful restoration of blurred images depends primarily on the knowledge about the degradationparameter.Defocus blur model in the frequency domain is characterized by concentric rings and the blurradius of the poin... Successful restoration of blurred images depends primarily on the knowledge about the degradationparameter.Defocus blur model in the frequency domain is characterized by concentric rings and the blurradius of the point spread function(PSF)can be identified conveniently in the frequency field for peopleby manual means rather than for computer.This paper introduces a practical method for computer to esti-mate the defocus blur parameter in cepstrum area.Fourier transform plays an intermediate role in the pathto cepstrum domain.We suggest a weighted adjustment operation in the frequency domain and then con-vert it to the cepstrum field to increase the accuracy of recognition. 展开更多
关键词 图象处理 参数识别 对数倒频谱 模糊图象
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INDIRECT DETERMINATION METHOD OF DYNAMIC FORCE BY USING CEPSTRUM ANALYSIS
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作者 吴淼 魏任之 《Journal of Coal Science & Engineering(China)》 1996年第2期75-80,共6页
The dynamic load spectrum is one of the most important basis of design and dynamic characteristics analysis of machines. But it is difficult to measure it on many occasions, especially for mining machines, due to thei... The dynamic load spectrum is one of the most important basis of design and dynamic characteristics analysis of machines. But it is difficult to measure it on many occasions, especially for mining machines, due to their bad working circumstances and high cost of measurements. For such situation, the load spectrum has to be obtained by indirect determination methods. A new method to identify the load spectrum, cepstrum analysis method, was presented in this paper. This method can be used to eliminate the filtering influence of transfer function to the response signals so that the load spectrum can be determined indirectly. The experimental and engineering actual examples indicates that this method has the advantages that the calculation is simple and the measurement is easy. 展开更多
关键词 振动模态分析 载荷谱 能量转换法 矿山
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基于模态理论和改进GMM的声发射源识别研究
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作者 杨勇 李晶 +1 位作者 朱作付 邓艾东 《电子器件》 CAS 2024年第1期128-133,共6页
基于模态声发射信号理论,提出了一种利用声学对数倒谱统计参数作为声发射信号特征参数的分析与提取方法。从声发射信号多模态特性出发,提出了一个基于改进高斯混合模型的声发射源信号识别系统。理论分析和实验结果表明,该方法能准确地... 基于模态声发射信号理论,提出了一种利用声学对数倒谱统计参数作为声发射信号特征参数的分析与提取方法。从声发射信号多模态特性出发,提出了一个基于改进高斯混合模型的声发射源信号识别系统。理论分析和实验结果表明,该方法能准确地判断声发射信号源,不仅能够应用于突发型声发射信号的识别,而且可以应用于连续型声发射信号的识别。 展开更多
关键词 声发射信号 倒谱 高斯混合模型 识别
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基于MFCC和GMM的瓷砖空鼓率识别系统及方法
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作者 周浩 梁军汀 卢杰 《无损检测》 CAS 2024年第3期28-32,55,共6页
针对瓷砖因内部空鼓而引起的松动、脱落等质量问题或其他安全隐患问题,研制了一套用于瓷砖空鼓率识别的试验系统。该系统采用梅尔倒谱系数(MFCC)法提取瓷砖敲击声的特征参数,再用高斯混合模型(GMM)法对MFCC特征参数进行分类和识别。试... 针对瓷砖因内部空鼓而引起的松动、脱落等质量问题或其他安全隐患问题,研制了一套用于瓷砖空鼓率识别的试验系统。该系统采用梅尔倒谱系数(MFCC)法提取瓷砖敲击声的特征参数,再用高斯混合模型(GMM)法对MFCC特征参数进行分类和识别。试验结果表明,采用MFCC和GMM相结合的方法,可以对瓷砖空鼓情况进行有效识别,该方法具有良好的应用前景。 展开更多
关键词 声纹识别 梅尔倒谱系数 混合高斯模型
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基于特征融合和B-SVM的鸟鸣声识别算法
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作者 陈晓 曾昭优 《声学技术》 CSCD 北大核心 2024年第1期119-126,共8页
为了实现在野外通过低成本嵌入式系统识别鸟类,提出了基于特征融合和B-SVM的鸟鸣声识别方法。对鸟鸣声信号提取梅尔频率倒谱系数、翻转梅尔频率倒谱系数、短时能量和短时过零率组成特征参数,通过线性判别算法对特征参数进行特征融合。... 为了实现在野外通过低成本嵌入式系统识别鸟类,提出了基于特征融合和B-SVM的鸟鸣声识别方法。对鸟鸣声信号提取梅尔频率倒谱系数、翻转梅尔频率倒谱系数、短时能量和短时过零率组成特征参数,通过线性判别算法对特征参数进行特征融合。利用黑寡妇算法通过测试集对支持向量机模型的核参数和损失值进行优化得到B-SVM模型。利用Xeno-canto鸟鸣声数据集对本文算法进行了测试,结果表明该方法的识别准确率为93.23%。算法维度参数的大小和融合特征维度的高低是影响算法识别效果的重要因素。在相同条件下,文中所提的基于特征融合和B-SVM模型的鸟鸣声识别算法相较于其他特征参数和模型,识别的准确率更高,为野外鸟类识别提供了参考。 展开更多
关键词 鸟鸣声识别 梅尔频率倒谱系数 线性判别算法 黑寡妇优化算法 支持向量机
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梅尔频率倒谱系数在声带息肉手术前后嗓音分析中的价值研究
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作者 刘茉 葛鑫颖 +2 位作者 赵晓畅 郝青青 李祖飞 《中国耳鼻咽喉颅底外科杂志》 CAS CSCD 2024年第2期102-105,共4页
目的 本研究拟通过提取患者嗓音中的梅尔频率倒谱系数(MFCC)指标,探讨其在声带息肉手术前后嗓音分析中的临床价值。方法 回顾性分析于2018年1月—2019年8月行声带息肉手术且术前及术后1个月均行嗓音评估的患者41例,男31例,女10例;平均年... 目的 本研究拟通过提取患者嗓音中的梅尔频率倒谱系数(MFCC)指标,探讨其在声带息肉手术前后嗓音分析中的临床价值。方法 回顾性分析于2018年1月—2019年8月行声带息肉手术且术前及术后1个月均行嗓音评估的患者41例,男31例,女10例;平均年龄(42.9±11.4)岁。另选取无声嘶且无声带病变的正常受试者21例作为基线对照。使用基于Python编程语言的librosa语音处理包进行MFCC特征提取,分别提取每位患者的MFCC均值,MFCC方差与MFCC标准差,使用配对样本t检验比较声带息肉手术前后上述各MFCC特征的差异。结果 声带息肉患者术后MFCC均值1.25±1.01、MFCC方差561.34±154.98及MFCC标准差21.74±4.03比术前MFCC均值6.81±2.05、MFCC方差1 019.66±295.87及MFCC标准差34.37±6.63显著下降,差异具有统计学意义(t=18.596,P=0.000;t=10.338,P=0.000;t=11.852,P=0.000)。声带息肉组患者术后1个月其MFCC均值、MFCC方差及MFCC标准差与正常受试者相比差异均无统计学意义,表明绝大部分声带息肉患者术后嗓音得到良好的恢复。结论 本研究首次探索了MFCC在声带息肉手术前后嗓音分析中的价值,MFCC各特征可作为评估声带息肉术后嗓音恢复的指标。 展开更多
关键词 声带息肉 声嘶 梅尔频率倒谱系数 嗓音分析 手术
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基于声音特征的隧道衬砌空洞识别方法研究
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作者 代晓景 暴学志 +2 位作者 柴雪松 周城光 阎兆立 《声学技术》 CSCD 北大核心 2024年第1期135-141,共7页
目前隧道衬砌空洞检测以人工敲击判断为主,检测过程中由于受到检测人员水平、注意力等主观因素影响,检测结果存在较大不确定性,因此有必要研制一种智能化的检测装置实现空洞自动识别。文章开展了衬砌空洞敲击回声智能识别算法研究,通过... 目前隧道衬砌空洞检测以人工敲击判断为主,检测过程中由于受到检测人员水平、注意力等主观因素影响,检测结果存在较大不确定性,因此有必要研制一种智能化的检测装置实现空洞自动识别。文章开展了衬砌空洞敲击回声智能识别算法研究,通过提取隧道衬砌冲击回波的梅尔倒谱系数(Mel Frequency Cepstral Coefficient,MFCC)作为特征,针对敲击回声脉冲信号长度不一的特点,提出了变帧长MFCC优化算法,并面向小样本条件,建立了支持向量机(Support Vector Machine,SVM)的识别模型。试验结果表明,该模型对衬砌空洞识别准确率可达89.9%。 展开更多
关键词 隧道衬砌空洞 声学信号处理 梅尔倒谱系数(MFCC) 支持向量机(SVM)
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倒频谱法在斜拉桥索力分析中的应用研究
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作者 贺博宙 邹兰林 《机械设计与制造》 北大核心 2024年第3期6-10,共5页
斜拉桥索力检测作为特大桥梁常规检测项目,应用非常广泛与频繁。现有常用检测方法为频率法,进行斜拉桥的索力检测过程中,经常会因拉索基频与塔台基频耦合,导致采集信号不理想,因而准确度较低,无法精准计算斜拉桥拉索索力。国外对于采样... 斜拉桥索力检测作为特大桥梁常规检测项目,应用非常广泛与频繁。现有常用检测方法为频率法,进行斜拉桥的索力检测过程中,经常会因拉索基频与塔台基频耦合,导致采集信号不理想,因而准确度较低,无法精准计算斜拉桥拉索索力。国外对于采样不理想的拉索进行分析时,通常利用多次采样或人工振动的方法来获取周期性更好的图像,操作繁琐并且精确度低,应用价值不高。因此,本研究针对采样信号不理想的问题采用倒频谱分析法对采集信号进行后处理。将复杂频谱图中的边频带转换为单条曲线,成功分离不同频率耦合的信号。通过对武汉二七长江大桥的实例分析验证,该索力检测法检验精度满足实际工程应用条件,且方法简便快捷,具有较高的实际应用价值。 展开更多
关键词 斜拉桥 索力检测 倒频谱 信号处理 MATLAB
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基于MFCC和随机森林的GIS动作声纹特征辨识和操作机构异常分类
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作者 庄小亮 李乾坤 +3 位作者 秦秉东 张长虹 张柳健 张禄亮 《电机与控制应用》 2024年第3期10-20,共11页
针对气体绝缘金属封闭开关(GIS)设备的操作机构异常或故障而导致其开关动作时出现分合闸失败或不到位的问题,提出了一种基于梅尔频率倒谱系数(MFCC)和随机森林的GIS设备操作机构异常分类模型。首先,对采集到的声纹信号进行预处理,使用M... 针对气体绝缘金属封闭开关(GIS)设备的操作机构异常或故障而导致其开关动作时出现分合闸失败或不到位的问题,提出了一种基于梅尔频率倒谱系数(MFCC)和随机森林的GIS设备操作机构异常分类模型。首先,对采集到的声纹信号进行预处理,使用MFCC提取声纹信号的特征;然后,构建随机森林对提取的特征信息进行辨识,得到GIS动作异常的分类结果;最后,以某110 kV的GIS设备为例,采集断路器、隔离开关的储能机构和传动机构异常或故障时的声纹信号,构建了音频样本库,并对所提分类模型与多种经典模型进行了对比测试。结果表明,MFCC能够有效提取出不同工况下GIS动作的声纹信号特征,且随机森林在众多分类识别模型中表现最优,有效提高了GIS动作异常工况识别的准确率。 展开更多
关键词 GIS动作异常 操作机构 声纹特征辨识 梅尔倒谱系数 随机森林
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基于双微麦克风阵列与WideResNet网络的语音命令词识别
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作者 祁潇潇 曾庆宁 赵学军 《计算机应用与软件》 北大核心 2024年第5期126-130,共5页
为了提高噪声环境下语音识别的稳健性[1],提出宽残差深度神经网络的语音识别算法。该算法结合双微麦克风阵列系统、语音数据集为双微麦克风数据集,使用功率归一化倒谱系数作为特征参数输入到残差网络中进行训练。实验表明,与ResNet15模... 为了提高噪声环境下语音识别的稳健性[1],提出宽残差深度神经网络的语音识别算法。该算法结合双微麦克风阵列系统、语音数据集为双微麦克风数据集,使用功率归一化倒谱系数作为特征参数输入到残差网络中进行训练。实验表明,与ResNet15模型、ResNet18模型相比,只有三个残差模块的宽残差网络在噪声环境下语音命令词的识别和内外部说话人检测任务中具有较高的准确度,均达到了95%以上。 展开更多
关键词 语音识别 宽残差神经网络 功率归一化倒谱系数 双微麦克风阵列
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Music/voice separation based on the multi-repeating structure of Mel cepstrum coefficient 被引量:4
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作者 ZHANG Tianqi XU Xin +1 位作者 WU Wangjun LIU Yu 《Chinese Journal of Acoustics》 CSCD 2015年第4期424-435,共12页
For the poor adaptability of the original repeating pattern, an improved music separation method of multi-repeating structure of Mel cepstrum coefficient (MFCC) is proposed. Firstly, the MFCC coefficient matrix (39... For the poor adaptability of the original repeating pattern, an improved music separation method of multi-repeating structure of Mel cepstrum coefficient (MFCC) is proposed. Firstly, the MFCC coefficient matrix (39-dimensional data) of the music signal was extracted. Then the cosine characteristic was applied to the count of similarity matrix of MFCC, and the fragments with consistent similarity are putted together. Next different repeating patterns are built for different groups. Thereby the spectrums of the background music and vocal were separated combined with ideal binary masking (IBM), and the corresponding time domain signals were obtained by inverse Fourier transform. Fnally, the improved method was tested on the music database of different types and length, and the separation results were compared with repeating method of Rafii and the non-negative matrix factorization based on flexible framework method of Ozerov. The experimental results showed that the separation performance of improved method was improved about 3 dB, and the performance of music with melody changed larger was significantly improved. Experiments verified that the improved method was an effective music separation algorithm and more stability. 展开更多
关键词 MFCC Music/voice separation based on the multi-repeating structure of Mel cepstrum coefficient Mel
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Voice conversion using structured Gaussian mixture model in cepstrum eigenspace 被引量:2
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作者 LI Yangchun YU Yibiao 《Chinese Journal of Acoustics》 CSCD 2015年第3期325-336,共12页
A new methodology of voice conversion in cepstrum eigenspace based on structured Gaussian mixture model is proposed for non-parallel corpora without joint training. For each speaker, the cepstrum features of speech ar... A new methodology of voice conversion in cepstrum eigenspace based on structured Gaussian mixture model is proposed for non-parallel corpora without joint training. For each speaker, the cepstrum features of speech are extracted, and mapped to the eigenspace which is formed by eigenvectors of its scatter matrix, thereby the Structured Gaussian Mixture Model in the EigenSpace (SGMM-ES) is trained. The source and target speaker's SGMM-ES are matched based on Acoustic Universal Structure (AUS) principle to achieve spectrum transform function. Experimental results show the speaker identification rate of conversion speech achieves 95.25%, and the value of average cepstrum distortion is 1.25 which is 0.8% and 7.3% higher than the performance of SGMM method respectively. ABX and MOS evaluations indicate the conversion performance is quite close to the traditional method under the parallel corpora condition. The results show the eigenspace based structured Gaussian mixture model for voice conversion under the non-parallel corpora is effective. 展开更多
关键词 LPCC Voice conversion using structured Gaussian mixture model in cepstrum eigenspace ES GMM
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基于改进MFCC算法的风力机叶片故障诊断方法
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作者 张家安 田家辉 +2 位作者 王铁成 邓强 梁涛 《太阳能学报》 EI CAS CSCD 北大核心 2024年第1期285-290,共6页
针对传统声信号特征处理方法无法有效提取叶片声音特征、导致叶片故障诊断准确率低的问题,提出一种基于改进梅尔频率倒谱系数(MFCC)算法的风力机叶片故障诊断方法。首先采用快速傅里叶变换(FFT)分析不同风速下叶片声音信号和风噪的频率... 针对传统声信号特征处理方法无法有效提取叶片声音特征、导致叶片故障诊断准确率低的问题,提出一种基于改进梅尔频率倒谱系数(MFCC)算法的风力机叶片故障诊断方法。首先采用快速傅里叶变换(FFT)分析不同风速下叶片声音信号和风噪的频率特性,明确叶片声音信号的频率分布区域,将全频段分为三部分;然后采用粒子群优化算法(PSO)对梅尔(Mel)函数在不同频段上的敏感度进行优化,在迭代过程中将MFCC算法提取的叶片声音特征进行聚类,以轮廓系数作为适应度函数;最后基于支持向量机(SVM)构建分类器,实现风力机叶片故障的准确识别。以华北某风电场的叶片声音采集数据为算例,考察该算法在不同风速工况下的适应性,验证该方法的有效性。 展开更多
关键词 风力机叶片 声信号处理 故障诊断 特征提取 梅尔频率倒谱系数
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基于MFCC的碳纤维复合缠绕气瓶损伤声发射信号分析
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作者 魏莱 龙飞飞 +1 位作者 杨可鑫 李沛莹 《无损检测》 CAS 2024年第4期53-58,共6页
针对碳纤维复合缠绕(CFPR)气瓶的损伤在线监测问题,对CFRP气瓶冲击损伤过程的声发射检测进行研究。以获取到的气瓶损伤声发射信号作为研究对象,通过梅尔倒谱系数(MFCC)特征提取方法,将原始信号转换为特征系数向量,将其参数值及变化趋势... 针对碳纤维复合缠绕(CFPR)气瓶的损伤在线监测问题,对CFRP气瓶冲击损伤过程的声发射检测进行研究。以获取到的气瓶损伤声发射信号作为研究对象,通过梅尔倒谱系数(MFCC)特征提取方法,将原始信号转换为特征系数向量,将其参数值及变化趋势进行同步比较。试验结果表明,不同损伤类型梅尔倒谱系数的分布呈现出明显的规律性。该研究结果可为CFPR材料的声发射检测信号识别提供一些参考。 展开更多
关键词 碳纤维复合缠绕气瓶 声发射 冲击 梅尔频率倒谱系数
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Power Cepstrum and Liftered Spectrum Analysis of Human Pulse Signal
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作者 王炳和 董彦武 +4 位作者 吴胜举 杨颙 相敬林 张效民 王海燕 《Chinese Science Bulletin》 SCIE EI CAS 1994年第8期681-686,共6页
The pulse condition is an important basis for diagnosis and treatment intraditional Chinese medicine. From ancient times, Chinese physicians have been ableto make out the pathological changes of the nine organs by pul... The pulse condition is an important basis for diagnosis and treatment intraditional Chinese medicine. From ancient times, Chinese physicians have been ableto make out the pathological changes of the nine organs by pulse-feeling andpalpation, based on the theory that the pathological mystique lies in the pulsecondition. Chinese physicians have obtained and identified all along the pulsecondition by their finger tips, so there have been inevitably many subjective factors 展开更多
关键词 PULSE SIGNAL POWER cepstrum and liftered SPECTRUM SPECTRAL characteristics.
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