《现代汉语语义词典》(Semantic Knowledge-base of Contemporary Chinese,简称SKCC)是一部机器可读的汉语语义词典。本文概括介绍SKCC的内容、特点并分析其主要缺点,尝试用莫斯科语义学派"意思文本"模式中的"支配模式&q...《现代汉语语义词典》(Semantic Knowledge-base of Contemporary Chinese,简称SKCC)是一部机器可读的汉语语义词典。本文概括介绍SKCC的内容、特点并分析其主要缺点,尝试用莫斯科语义学派"意思文本"模式中的"支配模式"来克服SKCC的不足。支配模式同时体现关键词用于所有义项时的语义、句法信息以及词义搭配的语义限制,应成为语义词典知识描述系统不可缺少的组成部分。展开更多
Aimed at the problem that Fourier decomposition method(FDM)is sensitive to noise and existing mode mixing cannot accurately extract gearbox fault features,a gear fault feature extraction method combining compound dict...Aimed at the problem that Fourier decomposition method(FDM)is sensitive to noise and existing mode mixing cannot accurately extract gearbox fault features,a gear fault feature extraction method combining compound dictionary noise reduction and optimized FDM(OFDM)is proposed.Firstly,the characteristics of the gear signals are used to construct a compound dictionary,and the orthogonal matching pursuit algorithm(OMP)is combined to reduce the noise of the vibration signal.Secondly,in order to overcome the mode mixing phenomenon occuring during the decomposition of FDM,a method of frequency band division based on the extremum of the spectrum is proposed to optimize the decomposition quality.Then,the OFDM is used to decompose the signal into several analytic Fourier intrinsic band functions(AFIBFs).Finally,the AFIBF with the largest correlation coefficient is selected for Hilbert envelope spectrum analysis.The fault feature frequencies of the vibration signal can be accurately extracted.The proposed method is validated through analyzing the gearbox fault simulation signal and the real vibration signals collected from an experimental gearbox.展开更多
文摘《现代汉语语义词典》(Semantic Knowledge-base of Contemporary Chinese,简称SKCC)是一部机器可读的汉语语义词典。本文概括介绍SKCC的内容、特点并分析其主要缺点,尝试用莫斯科语义学派"意思文本"模式中的"支配模式"来克服SKCC的不足。支配模式同时体现关键词用于所有义项时的语义、句法信息以及词义搭配的语义限制,应成为语义词典知识描述系统不可缺少的组成部分。
基金The National Natural Science Foundation of China(No.51975117)the Key Research&Development Program of Jiangsu Province(No.BE2019086).
文摘Aimed at the problem that Fourier decomposition method(FDM)is sensitive to noise and existing mode mixing cannot accurately extract gearbox fault features,a gear fault feature extraction method combining compound dictionary noise reduction and optimized FDM(OFDM)is proposed.Firstly,the characteristics of the gear signals are used to construct a compound dictionary,and the orthogonal matching pursuit algorithm(OMP)is combined to reduce the noise of the vibration signal.Secondly,in order to overcome the mode mixing phenomenon occuring during the decomposition of FDM,a method of frequency band division based on the extremum of the spectrum is proposed to optimize the decomposition quality.Then,the OFDM is used to decompose the signal into several analytic Fourier intrinsic band functions(AFIBFs).Finally,the AFIBF with the largest correlation coefficient is selected for Hilbert envelope spectrum analysis.The fault feature frequencies of the vibration signal can be accurately extracted.The proposed method is validated through analyzing the gearbox fault simulation signal and the real vibration signals collected from an experimental gearbox.
