磁巴克豪森噪声检测材料疲劳的励磁频率优化研究

磁巴克豪森噪声在铁磁性材料早期疲劳损伤的检测中具有巨大的应用潜力.在疲劳检测过程中,励磁频率作为磁巴克豪森噪声的激发源,对检测结果有重要影响.实验研究励磁频率对磁巴克豪森噪声检测铁磁性材料疲劳时检测结果的影响规律,以20R钢材料为对象进行低周疲劳实验,并在励磁频率分别为9,16,35,60?Hz下对取自同一母材的3个试...     

Barkhauseneigenspannungsmessungen an einem schadhaften Hydraulikzylinder mit tribotechnischer Funktionsschicht

Barkhausen Noise Analysis of a Tribofunctional Coated Hydraulic Cylinder with a Defect An airplane hydraulic cylinder showed a leak caused by a fatigue crack with its origin on the inside of the cylinder. The main reason for the development of the fatigue crack were regions with tiny cracks and residual tensile stresses produced during final machining of the cylinder base material. Residual stress differences on the inner surface were measured by Barkhausen noise analysis without removing the tribofunctional coating. The Barkhausen noise results were confirmed by some x-ray stress measurements.     

Application of 3D wavelet transforms for crack detection in rotor systems

The dynamics and diagnostics of a cracked rotor have been gaining importance in recent years. The early detection of faults like fatigue cracks in rotor shafts are very important to prevent catastrophic failure of the rotor system. Vibration monitoring during start up or shut-down is as important as during steady state operation to detect cracks especially for machines such as aircraft engines which start and stop quite frequently and run at high speeds. So, the transient data of the cracked rotor has been transformed using the wavelet transforms for crack detection. Most of the works quoted in the literature used 1D wavelets or 2D wavelets (Continuous Wavelet Transform-CWT) for crack detection. The crack detectors in the signals are both time as well as frequency dependent. So, the use of 2D wavelets is also not enough to detect the crack. In the present work a 3D wavelet (CWT) has been utilized which clearly indicates both the time and frequency features of the crack. The presence of sub-criticals in the CWT may be a best crack indicator but it is not always reliable. The addition of noise to the signal may sometimes lead to inaccurate results. So, there is a need to identify a parameter in addition to the sub-criticals. The phase angle between the two signals (cracked and un-cracked) or two transverse vibrations can be a better crack indicator because it is very less sensitive to noise disturbance. So, to extract the above phase angle a new transform has been applied called Cross Wavelet Transform (XWT). The XWT is exploited for the first time to a rotor fault detection system in the present work. Some interesting results have been obtained using the same. The advantage of the XWT is that both, the phase angles between the transverse signals and also the amplitudes of sub-criticals are viewed in a single plot. Parametric analysis is also carried out by varying crack depth and crack position for diagnostic purposes. The inverse problem of crack identification (i.e. determining the crack parameters through known vibration data) has also been carried out using Artificial Neural Network (ANN).     

Effect of Shot Peening Parameters to Residual Stress Profiles and Barkhausen Noise

The production of gear components includes numerous manufacturing operations which are carried out to ensure proper surface characteristics of components to deal with wear and fatigue. Surface shot peening is one way to increase the compressive residual stresses on the surface and thus ensure better wear and fatigue resistance. An experimental plan for shot peening was conducted to produce samples with varying surface characteristics. Residual stress profile and Barkhausen noise measurements were carried out for the samples. The objective of the study was to evaluate the interactions between the shot peening parameters studied, the residual stress profiles and the Barkhausen noise measurements. A multivariable regression analysis was applied for the task. Some remarkable correlations were found between the shot peening parameters, residual stress profile and Barkhausen noise features. The most important finding was that when the shot peening intensity was high enough, over 0.5 mmA, it dominated the shot peening coverage density parameter and thus no correlations could be gained. On the other hand, if the intensity parameter was lower than the limit of 0.5 mmA, the correlation between residual stress and Barkhausen noise measurements was remarkable. This means that the surface Barkhausen noise measurements could be used for the evaluation of the stress gradient in the shot peening process.     

基于小波变换的主动水声信号检测

信号检测是水声信号处理领域的研究重点之一。文章通过对水下航行器自噪声特性的研究，发现其具有1／f衰减特性，同时利用小波变换对1/f信号有类似K—L展开的作用，提出了一种基于小波变换的信号检测方法，对1/f噪声背景下的主动水声信号进行了检测；文中详细推导了相应的检验统计量及其统计分布特性；同时，将该方法与匹配滤波器、能量检测器的检测性能进行了比较，仿真试验结果表明了本方法的有效性。     

小波在应变测试中的应用

由于诸多因素的影响应变信号常常会含有高频干扰，这使得雨流法对结构进行疲劳统计的结果同实际情况有很大的偏差。本分析了小波滤波降噪的原理，并使用二进小波的方法成功地剔除了叠加在总长约8个小时的某应变信号中的高频成分，从而使得雨流法疲劳统计的结果同实际相符。本的分析结果表明小波能够用于振动信号的滤波降噪特别是对于应变信号中的高频干扰剔除，这对工程中的滤波降噪和疲劳统计有一定的参考价值。     

Detection of plastic deformation during fatigue of mild steel by the measurement of Barkhausen noise

In order to determine the potential of Barkhausen noise measurement as an ndt method, the effect of plastic deformation on the true RMS value of Barkhausen noise has been studied in a fine-grained mild steel. Due to cyclic straining, distinct changes in noise levels, the degree depending on the strain amplitude, occur even below the fatigue limit, indicating plastic deformation. It seems that by detecting the amount and variation during cycling, Barkhausen noise analysis could be used as an ndt method to predict the fatigue life of real steel structures without knowing their load levels.     

小波变换域双谱分析及其在滚动轴承故障诊断中的应用

工程信号不仅会受到高斯噪声干扰，而且也会受到非高斯噪声干扰。而传统双谱分析方法从理论上仅能抑制高斯噪声，但对非高斯噪声是无能为力的。针对传统双谱存在的不足，将小波变换和双谱分析结合，提出了一种基于小波变换域非参数化双谱故障诊断方法，并应用到滚动轴承故障诊断中。考虑到滚动轴承信号幅值调制特点，在本方法中，对处理信号采用了希尔伯特变换技术，以进行解调。实验结果表明，小波域双谱优于传统双谱，特别是在非高斯噪声情况下，小波域双谱更有优势；研究为滚动轴承故障诊断提供了一种新的有效方法。     

基于信号奇异性分析的轴承故障检测方法

针对轴承振动信号利用小波单奇异点检测无法克服噪声影响的不足,提出利用小波模极大值分析信号奇异性变化进而进行轴承故障检测的方法。实验中对信号的模极大分形指数,模极大分形指数熵,Lipschitz指数以及Lipschitz指数熵等奇异特征进行分析比较,实验结果表明这些特征都能有效克服噪声影响实现故障检测,但模极大曲线数最能体现故障特征且检测效果最好。将该方法同基于小波包能量谱特征和小波单奇异点检测的方法进行比较,结果表明本文建议的方法在检测时间及检测率上都有显著提高。     

滚动轴承振动信号的小波奇异性故障检测研究

该文以滚动轴承振动信号为分析对象 ,基于小波奇异性分析原理进行滚动轴承故障检测新方法的研究。通过求解待测信号的小波变换极大模来检测和识别信号中奇异点位置和奇异性大小 ,以及对噪声极大模的抑制处理 ,达到抑制或消除噪声的目的 ;最后 ,在剩余小波极大模的基础上进行信号重构 ,展现原待测信号中的故障信号模式。通过对铁路货车车轮用滚柱轴承振动信号的分析表明 ,此方法在大幅度地提高信噪比的同时 ,对由轴承损伤冲击造成的信号突变仍保持了较高的灵敏度和分辨率。为滚动轴承故障检测打下了良好的基础。     

基于小波系数非线性连续函数衰减的脑电信号去噪

环境噪声和工频噪声的干扰对脑电信号(EEG)的进一步处理和分析带来极为不利的影响。针对传统小波系数软阈值消噪方法去噪后产生的波形失真和硬阈值消噪方法去噪后产生的振荡现象,提出了一种新的小波系数非线性连续函数衰减处理算法。通过小波系数的非线性衰减处理,使低值端小波系数连续函数的变化介于硬软阈值函数之间,有效避免了处理后的波形失真和振荡。通过实验数据比较,证明处理后的脑电信号信噪比和均方误差均优于传统的小波去噪处理方法。     

分形噪声中谐波信号的提取

本文提出一种分形噪声中谐波信号的提取算法。它利用小波变换对1／f噪声的白化作用,结合自适应自调谐滤波器组,在小波域实现了分形噪声与谐波信号的分离。仿真结果表明,该算法能够有效地抑制分形噪声,显著地提高信噪比。     

小波包分形与支持向量机在水声目标识别中的应用研究

水声目标分类识别是公认的水声信号处理难题,船舶辐射噪声是一种非线性非平稳信号,具有一定的混沌特性,更好地认识船舶辐射噪声的非线性性质,有助于更好地寻找有效的水声目标检测及识别算法。为了解决水声目标的分类识别问题,提出了利用小波包分形和支持向量机组合进行水声目标识别。利用小波包分解得到目标辐射噪声不同频带内信号分形维数作为特征矢量,并输入到支持向量机实现目标分类,实验结果表明,小波包分形和支持向量机的结合有比较好的分类识别效果,有一定的实际应用价值。     

Magnetically Induced Potential Noise (MIPN)—A New Method for the Characterization of Magnetic Materials and for New Sensor Applications

Abstract

This paper discusses a new methodology for characterizing the magnetic properties of ferromagnetic materials. The method uses an alternating electric current to periodically magnetize ferromagnetic materials. The periodic magnetization generates a high-frequency electric potential noise between two electrodes within the excitation circuit. The magnetically induced electric potential noise (MIPN) is related to the discontinuous processes that occur during magnetization similar to magnetic Barkhausen noise. This paper discusses the results of several experiments that measured both electric potential noise and Barkhausen noise signal. A comparison of the results showed that the MIPN correlates directly to magnetic Barkhausen noise. The MIPN signal is small when compared to Barkhausen noise, but it is still easy to measure under laboratory conditions. Therefore, MIPN could be an efficient technique for materials characterization and sensor technology, for example, as fiber stress sensors in a composite aircraft component.     

Magnetically Induced Potential Noise (MIPN)—A New Method for the Characterization of Magnetic Materials and for New Sensor Applications

This paper discusses a new methodology for characterizing the magnetic properties of ferromagnetic materials. The method uses an alternating electric current to periodically magnetize ferromagnetic materials. The periodic magnetization generates a high-frequency electric potential noise between two electrodes within the excitation circuit. The magnetically induced electric potential noise (MIPN) is related to the discontinuous processes that occur during magnetization similar to magnetic Barkhausen noise. This paper discusses the results of several experiments that measured both electric potential noise and Barkhausen noise signal. A comparison of the results showed that the MIPN correlates directly to magnetic Barkhausen noise. The MIPN signal is small when compared to Barkhausen noise, but it is still easy to measure under laboratory conditions. Therefore, MIPN could be an efficient technique for materials characterization and sensor technology, for example, as fiber stress sensors in a composite aircraft component.     

Comparative analysis of genomic signal processing for microarray data clustering

Genomic signal processing is a new area of research that combines advanced digital signal processing methodologies for enhanced genetic data analysis. It has many promising applications in bioinformatics and next generation of healthcare systems, in particular, in the field of microarray data clustering. In this paper we present a comparative performance analysis of enhanced digital spectral analysis methods for robust clustering of gene expression across multiple microarray data samples. Three digital signal processing methods: linear predictive coding, wavelet decomposition, and fractal dimension are studied to provide a comparative evaluation of the clustering performance of these methods on several microarray datasets. The results of this study show that the fractal approach provides the best clustering accuracy compared to other digital signal processing and well known statistical methods.     

Fatigue behaviour of cast magnesium alloy AZ91 microstructurally modified by friction stir processing

Friction stir processing (FSP) was applied to cast magnesium alloy AZ91-F to modify the as-cast microstructure, and the effect of FSP on fatigue behaviour was discussed based on microstructural consideration, crack initiation, crack growth behaviour, and fracture surface analysis. Fully reversed axial fatigue tests have been performed using as-cast, T5-aged and their FSPed specimens (as-cast/FSP and T5/FSP). It was found that both FSPed specimens exhibited significantly higher fatigue strength than the as-cast and T5-aged specimens. FSP resulted in the break-up of coarse as-cast microstructure, grain refinement of the matrix, finely dispersed precipitates and increase of hardness, thereby both the crack initiation resistance and the crack growth resistance were considerably enhanced compared with the as-cast and T5-aged specimens, resulting in the improved fatigue strengths of the FSPed specimens.     

Stress Response of Magnetic Barkhausen Noise in Submarine Hull Steel: A Comparative Study

The development of magnetic Barkhausen noise methods for rapid detection of residual stress concentrations has implications for integrity assessment of submarine pressure hulls. However, the stress-response of Barkhausen noise in submarine hull steel, HY-80, is complicated by the influence of the material’s martensitic microstructure. The present work sheds light on the stress-dependent behavior of Barkhausen noise in HY-80 by comparing its signal characteristics with those of more common ferrite/pearlite steels. HY-80 and various ferrite/pearlite steel plates were uni-axially stressed up to and beyond the level for plastic deformation. Barkhausen noise measurements, performed using the same sensor under reproducible flux-controlled magnetization conditions, facilitated a direct comparison of material responses. Results showed that with the application of tensile stress, the Barkhausen noise signal of ferrite/pearlite steels linearly increased, reached a peak value and saturated in the elastic region. By contrast, HY-80 demonstrated a linear increase with tensile stress characterized by a transition from a lower to a seven times higher rate of change for stresses above 200 MPa up to its yield point. The different stress-response of HY-80 was attributed to its martensitic microstructure, which modifies the response of the domain structure under tensile stress conditions.     

Effect of internal hydrogen on very high cycle fatigue of precipitation-strengthened steel SUH660

The fatigue life of SUH660 steel is dominated by crack initiation in the region of very high cycle fatigue owing to the new crack initiation behavior near the tip of temporarily arrested crack. The effect of internal hydrogen on very high cycle fatigue life is investigated focused on crack initiation life via fatigue and Vickers hardness tests. Hydrogen inhibits cracks initiation, and accelerates the increase in crack initiation lives with decreasing stress in low and medium hardness zones. Hydrogen increases the hardness in low and medium hardness zones. Hydrogen extends new crack initiation lives and causes longer very high cycle fatigue life.