共查询到18条相似文献,搜索用时 265 毫秒
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高聿地 《机械工程与自动化》2011,(3)
圆度误差评定是否准确,将直接影响到机械产品的性能和寿命.介绍了4个简单而有效的算法来评定圆度误差,即最小外接圆、最大内接圆、最小区域法和最小二乘圆法.利用MATLAB对上述算法进行了验证,说明文中算法有效. 相似文献
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采用LabVIEW平台设计了基于虚拟仪器的圆度误差测量系统,实现了数据采集,数据分析与处理,实现了圆度误差最小二乘圆评定法算法,提高了圆度仪测量的速度和误差评定的自动化水平。 相似文献
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基于遗传算法的圆度公差评定法与采用最小二乘法评定的比较 总被引:4,自引:0,他引:4
根据提出的计算模型,对基于遗传算法的圆度误差评定和传统上采用最小二乘法的评定算法进行了比较分析,根据方法本身的特点和计算结果,分析了二者的不同点以及在工程应用中的适用场合.所构造的模型包括边界控制点和区域随机点,其中边界控制点模拟了由圆度误差最小区域条件所定义的最大内切圆和最小外切圆,而区域随机点模拟了实际情况下测试点的随机性和不确定性.计算结果表明基于遗传算法的圆度评定法精度较高,优于基于最小二乘法的评定算法. 相似文献
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最小二乘圆法评定圆度误差的程序设计 总被引:1,自引:0,他引:1
介绍了用最小二乘圆法评定圆度误差的准则及实现方法,在VC++环境下开发了圆度误差计算评定软件。测试验证表明,程序算法正确,界面直观形象,可直接显示圆度误差值和误差图形。 相似文献
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Kyung Joon Cha Kook-Hyun Yoo Chin Uk Lee Byeong Min Mun Suk Joo Bae 《Journal of Mechanical Science and Technology》2018,32(6):2453-2462
Harsh noises come from air-conditioning units are chronic complaining issues to their users. Individual perceptions of noise levels have been generally quantified by means of subjective evaluation such as a jury test. This article proposes a classification approach to acoustic noise signals using a wavelet spectrum analysis. We derive energy spectrums of noise signals using a discrete wavelet transform at pre-specified window length. The energy spectrums are a linear form and represented by a Hurst parameter as an informative summary of long-range dependent signal data. The Hurst parameter controls the self-similarity scaling as well as the degree of long-range dependence. We estimate the Hurst parameter through the least squares regression of sample energy against a resolution level in the wavelet spectral domain. In the context of multi-class classification problem, the classification of noise signals is performed by a nonlinear support vector machine (SVM) for parameter estimates of linear energy profiles containing the Hurst parameter. In an application example of air-conditioner noise signals, empirical results show that the proposed method offers the higher level of accuracy in acoustic noise sound classification. 相似文献
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传统的汽车节气门位置信号(throttle position sensor,TPS)处理方法不易消除发动机舱内电磁信号及周边环境的干扰。根据TPS的特征,在MATLAB中选用Daubechies五阶正交小波(dB5)对TPS噪声信号进行4层小波分解,再对分解后得到的各层系数用软阈值法量化处理,最后利用小波重构,实现对信号去噪。最后将获得的去噪信号用于发动机控制,并将控制结果与采用未去噪信号的发动机进行实车对比试验。试验表明:发动机采用去噪的TPS信号运行更平稳,小波变换后的去噪TPS信号对发动机控制具有良好的效果。 相似文献
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Duan Li-xiang Zhang Lai-bin Wang Zhao-hui 《Frontiers of Mechanical Engineering in China》2006,1(4):443-447
The vibration signals of diesel include excess noise that must be eliminated before extraction of characteristic parameters.
Firstly, the effects of vibration-signal de-noising among Fourier transform, wavelet decomposition and wavelet packet decomposition
are compared. Secondly, singular value decomposition is applied to de-noising vibration signals. Finally, a new de-noise method
integrated with wavelet packet and singular value is presented. In this method, vibration signals are decomposed by wavelet
packet, and the wavelet packet coefficient is de-noised by singular value decomposition again. The results indicate that the
new de-noising method is the best. The SNR (signal-to-noise ratio) of the vibration signals of a diesel cylinder lid is the
highest. The diesel vibration waveforms of combustion and valve become clear and the extracted characteristic parameters become
more precise.
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Translated from Journal of China University of Petroleum (Natural Science Edition), 2006, 30(1) (in Chinese) 相似文献
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新的基于小波变换的振动信号消噪方法 总被引:14,自引:0,他引:14
噪声消除是小波变换最成功的应用之一,其基本思想是将信号的小波变换系数与给定的门限比较,保留比门限大的系数,而将其他的置零,然后进行小波重构。这种小波变换消噪方法很可能将信号中一些有用的小能量分量当成噪声消除。根据旋转机械振动信号的循环平稳性特征,提出了一种新的基于小波变换的振动信号消噪方法,并用数字试验信号和碰摩试验振动信号对新消噪方法和Matlab提供的小波消噪方法的性能进行了比较测试。结果表明,在振动信号消噪方面,新方法相比传统的小波消噪方法有更好的性能,能够有效地抑制信号中处于各频段的噪声分量。 相似文献
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基于小波变换的盲信号分离的神经网络方法 总被引:8,自引:2,他引:8
提出一种新的盲信号分离的神经网络方法,该方法将小波变换和独立分量分析(ICA,Independent Component Analysis)相结合。利用小波变换的滤噪作用,将混合在原始信号中的部分高频噪声滤除后,再重构原始信号作为ICA的输入信号,有效地克服了现有ICA算法不能将噪声从源信号中分离的缺陷。实验结果表明,将该方法用于多通道脑电信号的盲分离是很有效的。 相似文献
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In order to extract fault features of large-scale power equipment from strong background noise, a hybrid fault diagnosis method based on the second generation wavelet de-noising (SGWD) and the local mean decomposition (LMD) is proposed in this paper. In this method, a de-noising algorithm of second generation wavelet transform (SGWT) using neighboring coefficients was employed as the pretreatment to remove noise in rotating machinery vibration signals by virtue of its good effect in enhancing the signal–noise ratio (SNR). Then, the LMD method is used to decompose the de-noised signals into several product functions (PFs). The PF corresponding to the faulty feature signal is selected according to the correlation coefficients criterion. Finally, the frequency spectrum is analyzed by applying the FFT to the selected PF. The proposed method is applied to analyze the vibration signals collected from an experimental gearbox and a real locomotive rolling bearing. The results demonstrate that the proposed method has better performances such as high SNR and fast convergence speed than the normal LMD method. 相似文献