Non-stationary signal analysis and transient machining process condition monitoring

Non-stationary machine condition monitoring is very important in modern automated manufacturing processes. In this research, an innovative non-stationary (transient) signal analysis approach has been developed for non-stationary machine condition monitoring. It is based on time–frequency distribution analysis and a singular value decomposition approach. The singular value decomposition method is used to extract features from the time–frequency distribution data. These features will serve as machine condition indices and can be easily incorporated for on-line machine condition monitoring and diagnosis. Satisfactory results have been obtained through simulation and experimental data. Experimental studies have demonstrated the effectiveness of the proposed method for transient machine and process condition monitoring.     

Time–energy density analysis based on wavelet transform

Energy is an important physical variable in signal analysis. The distribution of energy with the change of time and frequency can show the characteristics of a signal. A time–energy density analysis approach based on wavelet transform is proposed in this paper. This method can analyze the energy distribution of signal with the change of time in different frequency bands. Simulation and practical application of the proposed method to roller bearing with faults show that the time–energy density analysis approach can extract the fault characteristics from vibration signal efficiently.     

Fault detection and location in gears by the smoothed instantaneous power spectrum distribution

Time–frequency methods are effective tools for analysing diagnostics signals and have been widely used to describe machine condition. This paper introduces a time–frequency distribution, called the smoothed instantaneous power spectrum (SIPS) distribution, and demonstrates its use in the detection and location of local tooth defects in gears. The SIPS distribution is derived from the frequency domain definition of the instantaneous power spectrum (IPS) distribution, but has the added advantage that provides a considerable reduction in the ringing effect of the IPS transform, which results in a smoother and clearer time–frequency representation. A simulated gear vibration signal is used to show the capabilities of the proposed method over the IPS distribution and spectrogram. Healthy and faulty vibration signals monitored from a gear test rig are analysed, the results of which show that a local gear tooth defect can clearly be detected by the SIPS distribution.     

The application of the conditional moments analysis to gearbox fault detection—a comparative study using the spectrogram and scalogram

Time–frequency methods, which can lead to the clear identification of the nature of faults, are widely used to describe machine condition. Capabilities of time–frequency distributions in the detection of any abnormality can further be improved when their low-order frequency moments (or time-dependent parameters), which characterise dynamic behaviour of the observed signal with few parameters, are considered. This paper presents the applications of four time-dependent parameters (e.g. the instantaneous energy, mean and median frequencies, and bandwidth) based upon the use of spectrogram and scalogram, and compares their abilities in the detection and diagnosis of localised and wear gear failures. It has been found that scalogram based parameters are superior to those of a spectrogram in the detection and location of a local tooth defect even when the gear load is small, as they result in equally useful parameters in the revelation of gear wear. Moreover, the global values of these time-dependent parameters are found to be very useful and provide a very good basis for reflecting not only the presence of gear damage, but also any change in operating gear load.     

NDE of smart structures using multimode fiber optic vibration sensor

There are many conventional methods which may be used to monitor the health of structures — of which vibration monitoring is effective and can be used for special structures such as aircraft wings. A smart structure system based on fiber optic vibration sensors has been developed to monitor structural damage. A method based on the detection of spatial speckle of a multimode optical fiber is described. A multimode optical fiber with a diameter of 200/230 μm is used in the present experiment. The theoretical analysis and the experimental tests are described. The fiber optic sensors have been embedded in the carbon/epoxy composite specimens and surface mounted on the surface of aluminum specimens. Furthermore, experiments to examine the different types of damage to these specimens have been carried out. The results show that this kind of multimode fiber optic sensor can be used in the non-destructive evaluation of smart materials.     

Ultrasonic non-destructive evaluation with spatial combination of Wigner–Ville Transforms

This paper introduces a novel ultrasonic signal combination technique to be applied in detection systems based on multiple transducers. The technique uses a spatial combination approach that considers the specimen inspection from several apertures located in different planes. Information received from transducers is fused in a common integrated pattern with a signal to noise ratio (SNR) improvement. The result of the combination is a high quality image of the inspected material obtained from simple A-scans.The method is based on digital signal processing techniques, more concretely time–frequency analysis. Combination is performed by means of the Wigner–Ville Transform preserving temporal and frequencial information. Temporal techniques for combination are presented and the results obtained from both techniques are compared using the SNR.     

Ultrasonic NDE of composite material structures using wavelet coefficients

A wavelet-based method is proposed to perform the analysis of NDE ultrasonic signals received during the inspection of reinforced composite materials. The non-homogenous nature of such materials induces a very high level of structural noise which greatly complicates the interpretation of the NDE signals. By combining the time domain and the classical Fourier analysis, the wavelet transform provides simultaneously spectral representation and temporal order of the signal decomposition components. To construct a C-scan image from the wavelet transform of the A-scan signals, we propose a selection process of the wavelet coefficients, followed by an interpretation procedure based on a windowing process in the time–frequency domain. The proposed NDE method is tested on cryogenic glass/epoxy hydrogen reservoir samples.     

Determination of the cutoff frequency of an acoustic circumferential wave using a time–frequency analysis

In this article, time–frequency representation of Wigner–Ville is used to analyse the acoustic signal backscattered by a thin elastic tube of radii ratio b/a. This analysis allows to determine the reduced cutoff frequency of the circumferential antisymmetric wave A1 propagating around the tube. The evolution of this reduced cutoff frequency in function of b/a is reported. The values obtained of reduced cutoff frequency are compared to the values computed from the proper modes method.     

Determination of the group and phase velocities from time–frequency representation of Wigner–Ville

The experimental measurement of the group and phase velocities of some circumferential waves propagating around a thin elastic tube is a still complex operation. In this study, we show that the dispersion velocity can be determined from a time–frequency representation. We use the Wigner–Ville method by virtue of its interesting properties. On some time–frequency images, the symmetric (S0) and antisymmetric (A1) circumferential waves are identified. The group velocity dispersion estimated from these images is compared with that computed by the proper mode theory method. A good agreement is obtained. The phase velocity is also determined from the group velocity.     

Feature extraction of machine sound using wavelet and its application in fault diagnosis

Machine sound always carries information about the working of the machine. But in many cases, the sound has a very low SNR. To obtain correct information, the background noise has to be removed or the sound must be purified. A de-noising method is given in this paper and is successfully used in feature sound extraction. We can easily diagnose a machine using the purified sound. This de-noising method is based on the wavelet technique and uses the Morlet wavelet as the mother wavelet, because its time–frequency resolution can be adjusted to adapt to the signal to be analyzed. The method is used for extracting the sound of some vehicle engines with different types of failure. The feature sound is extracted successfully.     

Improving the time resolution and signal noise ratio of ultrasonic testing of welds by the wavelet packet

In ultrasonic testing of welds, detection of small flaws is often difficult by the superimposed noise due to the grain structure of the material. The scattering of ultrasonic waves from grain boundaries can interfere and introduce disturbance in the received signal that can sometimes mask indications due to a small but potentially dangerous defect. However, to enhance the flaw characterization, methods based on ‘thresholding’ have given good results only when the signal to noise ratio is high, and since bandwidth of the reflected signal as well as its principal frequency is subject to wide variation, it is impossible to create an appropriate band pass filter. So linear filtering does not provide good results, because both, the structure noise and flaw signal concentrate energy in the same frequency band. Non-linear filtering can be used to reduce or suppress the noise from ultrasonic signals. One way out is to use the time frequency transforms, the method is based on the wavelet packet decomposition. The Debauchee function of order 8 [Daubauchee I. Orthogonal bases of capacity wavelets. Commun Pure Appl Math 1998;41] has been chosen as the analyzing function, and each measured ultrasonic signal is analyzed by a filter bank through only three levels of decomposition. This work demonstrates that the following analysis is very efficient with respect to signal recovery from noisy data. The experimental results have shown that the proposed method has excellent performances on SNR enhancements.     

Fatigue crack monitoring of riveted aluminium strap joints by Lamb wave analysis and acoustic emission measurement techniques

Statistics show that fatigue crack development comes first and foremost as a damage source in aerospace metallic structures. Currently, widespread methods are available to inspect these structures, but they are quite time-consuming, costly and require the structural system to be idle. Next, attempts to develop damage detection integrated systems are paramount for the safety and cost of such structures. This paper describes an investigation into the feasibility of using an integrated system based on Lamb waves in order to assess the integrity of riveted aluminium joints during cyclical loading. In this experimental analysis, Lamb waves are excited and received outside the joint area using piezoelectric transducers coupled onto the plates. The detected damage is cracks in joint resulting from fatigue loading. The collected signals on the piezoelectric transducers are analysed using Hilbert transform and time–frequency analysis. It is shown that the final interpretation of Lamb wave analysis may provide a means of sizing the defects and following the crack development. In addition to that, an acoustic emission system is used jointly with the Lamb wave analysis in order to discuss results and damage development. Finally, it is demonstrated that both methods can work together and the results obtained are in good agreement.     

Optimization of antenna configuration in multiple-frequency ground penetrating radar system for railroad substructure assessment

This paper discusses the use of ground penetrating radar (GPR) to rapidly, effectively, and continuously assess railroad track substructure conditions, especially ballast. To overcome the limited electromagnetic waves penetration for high-frequency antennae and the low resolution of low-frequency antennae, this study uses a multiple-frequency GPR system to assess railroad substructure conditions. High-frequency antennae were used to detect the scattering pattern, which is related to air void volume in railroad ballast, and low-frequency antennae are used to assess deeper substructure conditions. Considering the scattering energy attenuation is highly frequency and material dependent, a time–frequency method based on tracking the frequency spectrum and energy change over depth can be used to extract ballast fouling conditions. From GPR field collected data, ground-truth observation, and ballast gradation analysis, the multiple-frequency GPR system demonstrates a promising capability to assess railroad track substructure condition.     

波信号的解调和人工神经网络的损伤识别算法(英文)

讨论了基于波信号的解调和人工神经网络的损伤识别算法,以及其在Lamb波信号的应用。Lamb波与损伤相互作用,将修改回波信号,从该信息提取相关的损害信息可用于自动损伤检测。然而,由于该波与损害相互作用的复杂性,波信号的反应是不容易解释。反应的波信号被认为是一个高频率载波信号调制的低频信号。基线减法后,频域卷积和滤波,原来的信号解调成一个新的简单的信号,其与因损伤发生的能量变化有关。随后进行特征提取,通过寻找新信号的局部极大值和所取得的峰值和位置将作为人工神经网络的损伤特性的输入。这种损伤检测验证算法的有效性,通过一个带缺口复合材料层压板缺损模型利用有限元进行验证。对不同缺口深度和位置的反应波信号用于模拟和训练和测试的样本。最后,对网络的精度和泛化能力进行评估,结果是令人满意的。     

On-line detection of the breakage of small diameter drills using current signature wavelet transform

This paper presents on-line tool breakage detection of small diameter drills by monitoring the AC servo motor current. The continuous wavelet transform was used to decompose the spindle AC servo motor current signal and the discrete wavelet transform was used to decompose the feed AC servo motor current signal in time–frequency domain. The tool breakage features were extracted from the decomposed signals. Experimental results show that the proposed monitoring system possessed an excellent on-line capability; in addition, it had a low sensitivity to change of the cutting conditions and high success rate for the detection of the breakage of small diameter drills.     

Forced vibration behaviour and crack detection of cracked beams using instantaneous frequency

In this paper, a new method for crack detection in beams based on instantaneous frequency and empirical mode decomposition is proposed. The dynamic behaviour of a cantilever beam with a breathing crack under harmonic excitation is investigated both theoretically and experimentally. A simple single-degree-of-freedom system with varying stiffness is employed to simulate the dynamic behaviour of the beam. The time-varying stiffness is modelled using a simple periodic function. Both simulated and experimental response data are analysed by applying empirical mode decomposition and Hilbert transform and the instantaneous frequency of each oscillatory mode is obtained. It is shown that the instantaneous frequency oscillates between frequencies corresponding to the open and closed states revealing the breathing of the crack. The variation of the instantaneous frequency increases with increasing crack depth following a polynomial law and consequently can be used for estimation of crack size. Using the intrinsic modes of the system, the harmonic distortion of the distorted sinusoidal response is calculated. It follows that the harmonic distortion increases with crack depth following definite trends and can be also used as an effective indicator for crack size. The proposed time–frequency approach is superior compared to Fourier analysis and can be used to improve the effectiveness of vibration-based crack detection techniques.     

Rolling element bearing fault diagnosis using wavelet packets

A method is proposed for the analysis of vibration signals resulting from bearings with localized defects using the wavelet packet transform (WPT) as a systematic tool. A time–frequency decomposition of vibration signals is provided and the components carrying the important diagnostic information are selected for further processing. The proposed method is designed in such a way that it can exploit the underlying physical concepts of the modulation mechanism, present in the vibration response of faulty bearings. The flexibility of the WPT and the systematic parameter selection criteria, help in the minimization of interventions by the end user. The method is evaluated using simulated and experimental signals.     

Low frequency bending piezoelectric actuator with integrated ultrasonic NDE functionality

A bending piezoelectric actuator has been manufactured with a 250 μm thick PZT plate embedded in five layers of unidirectional fiber Kevlar epoxy. The selected orientation of the fibers produces a gradient of residual stresses in the composite that enhances bending actuation. By segmenting the electrodes, it is possible to launch an ultrasonic pulse in the actuator so that structural health monitoring of the actuator itself can be performed using pitch catch ultrasonic NDE during the low frequency actuation. Qualitative experimental results of fatigue tests and damage detection are presented.     

Wave propagation in thin Plexiglas plates: implications for Rayleigh waves

Two-dimensional (2D) experimental models are often used to study wave propagation problems. The advantages of using 2D experimental models, as opposed to 3D models, is the reduction of both extraneous reflections and mathematical complexity. Further, many structural elements conform to this geometry. The following study examines Rayleigh wave motion in thin Plexiglas sheets. Source–receiver time domain measurements were made at different locations on the Plexiglas sheet. The time–distance space was 2D-Fourier transformed into the frequency–wavenumber space to facilitate the analysis of wave modes propagating in the Plexiglas sheet. Experimental results showed that fundamental symmetric (S₀) and antisymmetric (A₀) Lamb waves propagated through the plate. Along the thickness of the plate, a non-dispersive Rayleigh wave was generated. Lamb waves were found to interfere with the Rayleigh wave. The assumption of generalized plane stress is preserved if higher mode Lamb waves have low energy content.