共查询到19条相似文献,搜索用时 171 毫秒
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提出了一种利用检测进给电机电流实现切削加工过程中刀具破损的在线监控系统.在该系统中,离散小波分析技术被用来实现对电机电流信号的处理,并有效地提取了刀具破损时的特征;探讨了中断型宏指令功能在刀具破损在线监控系统中的应用;经实践证明,利用该监测系统和中断型宏指令,能够实时的识别加工过程刀具的破损,并能及时报警、自动换刀等,机床的故障停机时间大大减少,利用率得到了提高. 相似文献
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提出一种基于小波变换和傅立叶变换综合测量电参量的新方法.首先利用小波变换对谐波信号作预处理.消除谐波信号中的噪声以及分离信号中的暂态分量,然后通过小波变换重构信号并对其进行快速傅立叶变换,最后根据Budeanu定义的电参量计算公式就可以很方便的计算出各电参量.仿真结果表明,该方法能够更精确的测量出各电参量. 相似文献
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选用Morlet小波基函数,将连续小波变换分别应用于时域同步平均信号和齿轮啮合残余信号.对比分析了正常齿轮、微小裂纹齿轮和破损齿轮的小波功率谱和最大小波功率谱,发现齿轮啮合残余信号的小波功率谱和最大小波功率谱对微小裂纹较敏感,能较早地诊断齿轮裂纹的出现.提取小波功率最大值及其与平均值的比值,作为诊断齿轮裂纹出现和进展的量化指标,并作了分析验证.对比分析了齿轮振动时域同步平均信号和啮合残余信号的时域波形和傅立叶频谱,均不能及时诊断微小裂纹. 相似文献
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数控机床刀具磨损监测实验数据处理方法研究 总被引:3,自引:0,他引:3
数控机床刀具磨损监测对于提高数控机床利用率,减小由于刀具破损而造成的经济损失具有重要意义.有针对性地回顾了国内外各种分析刀具磨损信号方法的研究工作,详细叙述了功率谱分析法、小波变换、人工神经网络以及多传感器信息融合技术的实现形式.通过比较各种数据处理方法的优缺点,提出基于混合智能多传感器信息融合技术是数控机床刀具磨损监测实验数据处理的未来发展的主要方向. 相似文献
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基于小波变换切削力信号监控PCBN刀具破损的研究 总被引:3,自引:1,他引:3
阐述了小波分析及小波去噪的基本理论,针对傅氏变换和短时傅氏变换的缺点,提出了基于小波变换的切削力信号分析方法。小波多分辨分析能够实现PCBN刀具切削力信号的任意精度与尺度的时一频域分解,从而判断PCBN刀具的切削状态,根据切削力信号的不同特征及时调整切削参数,减少刀具破损的发生,并能够揭示典型切削力信号的分布特征。 相似文献
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基于Shannon小波能量熵与FFT的电力系统谐波检测方法研究 总被引:1,自引:0,他引:1
利用小波变换的频带划分能力和小波熵对扰动信号检测能力,结合傅立叶变换准确的频域分辨能力,提出一种基于傅立叶变换及小波能量熵联合的电力系统谐波检测改进算法。分析了快速小波变换中小波混叠产生的原因,并提出解决方法。根据电力系统谐波的特点,建立谐波信号数学模型,基于该模型利用Matlab对算法进行仿真验证;利用DSP实验台,对改进算法进行实用化测试。 相似文献
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Dr Xiaoli Li 《The International Journal of Advanced Manufacturing Technology》1998,14(8):539-543
This paper presents a real-time tool breakage detection method for small diameter drills using acoustic emission (AE) and current signals. Using the transmitted properties of the AE signal, apparatus for detecting the AE signal for tool breakage monitoring was developed for a machine centre. The features of tool breakage were obtained from the AE signal using typical signal processing methods. The continuous wavelet transform (CWT) and the discrete wavelet transform (DWT) were used to decompose the spindle current signal and the feed current signal, respectively. The tool breakage features were extracted from the decomposed signals. Experimental results show that the proposed monitoring system possessed an excellent real-time capability and a high success rate for the detection of the breakage of small diameter drills using combined AE and current signals. 相似文献
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利用连续小波变换对模拟瞬变信号进行了仿真 ,试验结果表明 ,此方法灵敏度高 ,对噪声具有较好的鲁棒性。在此基础上探讨了基于离散小波变换的刀具破损的检测情况 ,取得了较好的效果 ,解决了以往此类故障由于干扰大而难以识别的困难 ,为故障诊断领域提供了一种非常有效的手段 相似文献
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P. Y. Sevilla-Camacho G. Herrera-Ruiz J. B. Robles-Ocampo J. C. Jáuregui-Correa 《The International Journal of Advanced Manufacturing Technology》2011,53(9-12):1141-1148
Tool condition monitoring, mainly tool breakage detection for high-speed machining (HSM), is an important problem to solve; however, the techniques or types of sensors applied in other research projects present certain inconveniences. In order to improve tool breakage monitoring systems, a simple, effective, and fast method is presented herein. This method is based on the discrete wavelet transform (DWT) and statistical methodologies. The effectiveness of the method is based on the measurements of the feed-motor current signals using inexpensive sensors. It is well-known that during the cutting process, the motor current is related to the tool condition. The current consumption changes when the tool is broken as compared to when the tool is in normal cutting condition. This difference can be obtained from the waveform variances between the signals in order to ascertain the tool condition. The algorithms of this research project consist of obtaining compressed signals from the I rms feed-motor current signals applying the DWT. Then from these compressed signals, we detect the asymmetries between them. The arithmetic mean value is applied to asymmetries of consecutive machining lengths to reduce noise in the data having a mean value of a series of asymmetries; also, a normal cutting threshold is set up in order to make decisions regarding the tool conditions so as to detect tool breakage. Therefore, this research project shows a low-cost monitoring system that is simple to implement. 相似文献
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Application of the Discrete Wavelet Transform to the Monitoring of Tool Failure in End Milling Using the Spindle Motor Current 总被引:3,自引:3,他引:0
The paper presents an application of the discrete wavelet transform to the monitoring of tool failure in end milling operations
using the spindle motor current. The discrete wave-let transform performs a multilevel signal decomposition to extract the
tool failure feature from the spindle motor current. Experimental results have shown that tool failure in end milling operations
can be clearly detected even under varying cutting conditions. 相似文献
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基于EMD和支持向量机的柴油机故障诊断 总被引:6,自引:1,他引:5
为了解决传统小波或小波包变换方法对柴油机振动信号频率分辨率不高、易受邻近谐波分量间交叠影响的缺陷,提出了一种基于经验模态分解和支持向量机的故障诊断方法。该方法首先对振动信号进行经验模态分解,分别提取能量最大的几个基本模式分量的小波包特征;然后采用支持向量机在每个独立的特征子集中进行训练,并按该子集对应的基本模式分量的能量权重进行加权融合。试验中将该方法应用于6135型柴油机的故障诊断,结果表明,针对每个基本模式分量分别进行故障分析是可行的,能够对6135型柴油机常见故障模式进行准确识别。 相似文献
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HHT在Lamb波检测信号分析中的应用 总被引:1,自引:0,他引:1
将一种新的超声信号处理技术用于Lamb波波形中多个模式到达时间的提取。通过将希尔伯特-黄变换(Hilbert-Huang transform,简称HHT)与快速傅里叶变换(fast Fourier transform,简称FFT)、小波变换(wavelettransform,简称WT)在时频分辨率方面的比较,表明HHT能够精确识别信号中两种频率分量突变的时刻,显示了HHT方法的优越性。将HHT方法的特性用于Lamb波模式到达时间的提取,从HHT的能量-时间图上可以看出,能量峰值时刻对应着各Lamb波模式的到达时间。试验结果与理论值具有较好的一致性。 相似文献