Fatigue crack visualization using noncontact laser ultrasonics and state space geometrical changes

Rotating shafts operating under complex loading conditions are susceptible to develop fatigue cracks at the localized stress concentration points. Fatigue cracks are the prime sources for catastrophic failures. Therefore, it is vital and challenging for the early fatigue crack detection to prevent costly machinery breakdowns. A rotor test rig with a facility of introducing stochastic loads on to the rotating shaft is designed and developed to induce fatigue crack on the shaft is utilized for this study. Accelerated fatigue tests are performed, along by introducing stochastic loads, on a shaft specimen seeded with circumferential V-notch configuration. The methodology for early crack detection is based on analyzing the steady-state vibration data acquired, till the shaft specimen develops fatigue crack, from various locations of the test rig using different sensors like miniature accelerometers, wireless telemetry strain gauge, and laser vibrometer. In the present study, signal processing tools like continuous wavelet transforms (CWT), Hilbert–Huang transform (HHT), and short-time Fourier transform (STFT) are employed for the early fatigue crack detection. Wavelet packet (WP) analysis is used to decompose the experimental vibration response data into narrow frequency band signals before the processing of CWT, HHT, and STFT analyses. In addition, these techniques are compared to evaluate their detection performance when employed directly on raw data and preprocessed data using WP analysis. Finally, this paper provides a detailed description and comprehensive selection of time-frequency techniques for the early fatigue crack detection.

Fatigue crack detection using dual laser induced nonlinear ultrasonic modulation

Noncontact detection of fatigue cracks by laser nonlinear wave modulation spectroscopy (LNWMS)

Acoustic emission (AE) monitoring technique is a well-known approach in the field of NDE/SHM. AE monitoring from the defect formation and failure in the materials were well studied by the researchers. However, conventional AE monitoring techniques are predominantly based on statistical analysis. In this study we focus on understanding the AE waveforms from the fatigue crack growth using physics based approach. The growth of the fatigue crack causes the acoustic emission in the material that propagates in the structure. One of the main challenges of this approach is to develop the physics based understanding of the AE source itself. The acoustic emission happens not only from the crack growth but also from the interaction of the crack lips during fatigue loading of the materials. As the waveforms are generated from the AE event, they propagate and create local vibration modes along the crack faces. Fatigue experiments were performed to generate the fatigue cracks. Several test specimens were used in the fatigue experiments and corresponding AE waveforms were captured. The AE waveforms were analyzed and distinguished into different groups based on the similar nature on both time domain and frequency domain. The experimental results are explained based on the physical observation of the specimen.

Early predator detection is a key component of the predator-prey arms race and has driven the evolution of multiple animal hearing systems. Katydids (Insecta) have sophisticated ears, each consisting of paired tympana on each foreleg that receive sound both externally, through the air, and internally via a narrowing ear canal running through the leg from an acoustic spiracle on the thorax. These ears are pressure-time difference receivers capable of sensitive and accurate directional hearing across a wide frequency range. Many katydid species have cuticular pinnae which form cavities around the outer tympanal surfaces, but their function is unknown. We investigated pinnal function in the katydid Copiphora gorgonensis by combining experimental biophysics and numerical modelling using 3D ear geometries. We found that the pinnae in C. gorgonensis do not assist in directional hearing for conspecific call frequencies, but instead act as ultrasound detectors. Pinnae induced large sound pressure gains (20–30 dB) that enhanced sound detection at high ultrasonic frequencies (>60 kHz), matching the echolocation range of co-occurring insectivorous gleaning bats. These findings were supported by behavioural and neural audiograms and pinnal cavity resonances from live specimens, and comparisons with the pinnal mechanics of sympatric katydid species, which together suggest that katydid pinnae primarily evolved for the enhanced detection of predatory bats.

This paper presents a fatigue crack detection technique using changes of linear ultrasonic features caused by structural nonlinearity. We theoretically and experimentally demonstrate that a nonlinear mechanism produced by a fatigue crack not only generates nonlinear modulations or harmonics, but also reduces the amplitude of the linear responses because the energy in the linear responses is partially transmitted to the harmonic or modulation components. The experimental results show that the amplitude reduction of the linear responses is more sensitive to a fatigue crack than the amplitude increase of the harmonics and modulation components. In addition, a baseline-free fatigue crack detection technique is proposed considering the additional amplitude reduction of the linear components due to nonlinear ultrasonic modulation.

Bending fatigue crack is a dangerous and insidious mode of failure in gears. As it produces no debris in its early stages, it gives little warning during its progression, and usually results in either immediate loss of serviceability or greatly reduced power transmitting capacity. This paper presents the applications of vibration-based techniques (i.e. conventional time and frequency domain analysis, cepstrum, and continuous wavelet transform) to real gear vibrations in the early detection, diagnosis and advancement monitoring of a real tooth fatigue crack and compares their detection and diagnostic capabilities on the basis of experimental results. Gear fatigue damage is achieved under heavy-loading conditions and the gearbox is allowed to run until the gears suffer badly from complete tooth breakage. It has been found that the initiation and progression of fatigue crack cannot be easily detected by conventional time and frequency domain approaches until the fault is significantly developed. On the contrary, the wavelet transform is quite sensitive to any change in gear vibration and reveals fault features earlier than other methods considered.

This paper presents a method to measure responses for a sinusoidally excited structure using a continuously scanning Laser Doppler Vibrometer (LDV). The LDV output signal is an amplitude-modulated vibration, whereby the excitation signal will be modulated by the response of the excited structure. Using an applicable demodulation the mode shape defined along a scan line can be derived by the envelope of the modulated vibration. By using an adaptable digital low-pass filter and parallel measuring of responses and mirror drive signal in the time domain the mode shape can be directly derived from the measured response. So the demodulation is a fast method to identify the mode shape from the measured response, because of its completion in the time domain. For that purpose the method is capable for using the responses online for normal mode tuning. Furthermore it is necessary for normal mode testing to measure complex responses to make an affirmation about the separation of real mode shapes. The method will match these requirements.

Mechanical fastening is still one of the main methods used for joining components. Different techniques have been applied to reduce the effect of stress concentration of notches like fastener holes. In this work we evaluate the feasibility of combining laser shock peening (LSP) and cold expansion to improve fatigue crack initiation and propagation of open hole specimens made of 6061-T6 aluminum alloy. LSP is a new and competitive technique for strengthening metals, and like cold expansion, induces a compressive residual stress field that improves fatigue, wear and corrosion resistance. For LSP treatment, a Q-switched Nd:YAG laser with infrared radiation was used. Residual stress distribution as a function of depth was determined by the contour method. Compact tension specimens with a hole at the notch tip were subjected to LSP process and cold expansion and then tested under cyclic loading with R=0.1 generating fatigue cracks on the hole surface. Fatigue crack initiation and growth is analyzed and associated with the residual stress distribution generated by both treatments. It is observed that both methods are complementary; cold expansion increases fatigue crack initiation life, while LSP reduces fatigue crack growth rate.

Integrity of in-service engineering structures is prone to fatigue damage over their lifespan. Majority of the currently existing elastic-wave-based damage identification techniques have been developed and validated for damage at macroscopic levels, by canvassing linear properties of elastic waves such as attenuation, transmission, reflection and mode conversion. However the real damage in engineering structures often initiates from fatigue crack, presenting highly nonlinear characteristics under cyclic loads. It is of great significance but vast challenge to detect fatigue damage of small dimension at its initial stage. In this study, traditional elastic-wave-based damage identification techniques were first employed with an attempt to detect fatigue crack initiated from a notch in an aluminium plate with the assistance of a signal correlation analysis, to observe the deficiency of the approach. Then the higher-order harmonic wave generation was used to exploit the nonlinear characteristics of acousto-ultrasonic waves (Lamb waves), whereby the fatigue damage was characterised. Results show that nonlinear characteristics of acousto-ultrasonic waves can facilitate more effective detection of fatigue damage than linear signal features such as wave reflection, transmission or mode conversion.

Fatigue damage prognosis of steel bridges under traffic loading using a time-based crack growth method

The autoregressive analysis of stationary multivariate time series includes construction of a time domain model in the form of a multivariate stochastic difference equation and its transformation into a spectral matrix to study frequency domain properties. The time series is treated as a linear system with one output process and one or several inputs. This approach provides an explicit time domain description of the time series as a function of the past of output and input components. In the bivariate case, the frequency domain results include spectral densities, coherent spectrum, coherence function, and gain and phase factors. The coherence function shows the degree of linear interdependence, the coherent spectrum presents the contribution of the input component to the output, the gain factor consists of amplification coefficients, and the phase factor describes lags between the time series. All these quantities are frequency dependent. The Granger causality concept and feedbacks within the system are discussed as a part of bivariate time and frequency domain analysis. Some comments are given regarding the software for parametric analysis of multivariate time series. The use of cross-correlation coefficient and regression equation for describing dependence between time series or for reconstructing them is shown to be incorrect.

Epilepsy is a neurological disorder that causes seizures of many different types. Recent research has shown that epileptic seizures can be predicted by using the electrocardiogrami instead of the electroencephalogram. In this study, we used the heart rate variability that is generated by the fluctuating balance of sympathetic and parasympathetic nervous systems to predict epileptic seizures. We studied 11 epilepsy patients to predict the seizure interval. With regar tos the fact that HRV signals are nonstationary, our analysis focused on linear features in the time and frequency domain of HRV signal such as RR Interval (RRI), mean heart rate (HR), high-frequency (HF) (0.15-0.40 Hz) and low-frequency (LF) (0.04-0.15 Hz), as well as LF/HF. Also, quantitative analyses of Poincaré plot features (SD1, SD2, and SD1/SD2 ratio) were performed. HRV signal was divided into intervals of 5 minutes. In each segment linear and nonlinear features were extracted and then the amount of each segment compared to the previous segment using a threshold. Finally, we evaluated the performance of our method using specificity and sensitivity. During seizures, mean HR, LF/HF, and SD2/SD1 ratio significantly increased while RRI significantly decreased. Significant differences between two groups were identified for several HRV features. Therefore, these parameters can be used as a useful feature to discriminate a seizure from a non-seizure The seizure prediction algorithm proposed based on HRV achieved 88.3% sensitivity and 86.2 % specificity. These results indicate that the HRV signal contains valuable information and can be a predictor for epilepsy seizure. Although our results in comparison with EEG ares a little bit weaker, the recording of ECG is much easier and faster than EEG. Also, our finding showed the results of this study are considerably better than recent research based on ECG (Tab. 1, Fig. 10, Ref. 17).

Determining the air bearing frequencies is important and essential to understand the complex flying performances of slider. However, in typical flying height test, it is usually difficult to distinguish the air bearing frequencies in the experimental data, especially when the slider is in full flying state. In such a case, it is optional to employ simulation to help determine the air bearing frequencies and their harmonic components. This paper performs both time and frequency domain simulations to analyze air bearing frequencies of a pemto slider and compare the results with experimental data obtained using laser Doppler vibrometer. It is found that the simulation results are well correlated with the experimental results. Time domain simulation provides not only the air bearing frequencies, but also the harmonic frequencies. Frequency domain simulation, on the other hand, provides clear identification of the three dominant air bearing frequencies, with additional information such as air bearing stiffness and damping obtainable. It is suggested that simulations in both time and frequency domains should be conducted to assist in determining the air bearing frequencies and their harmonic components.

Damping is largely increasing with the vibration amplitude during nonlinear vibrations of rectangular plates. At the same time, soft materials present an increase of their stiffness with the vibration frequency. These two phenomena appear together and are both explained in the framework of the viscoelasticity. While the literature on nonlinear vibrations of plates is very large, these aspects are rarely addressed. The present study uses the fractional solid model to describe the viscoelastic material behaviour. This allows to capture at the same time (i) the increase in the storage modulus with the vibration frequency and (ii) the frequency-dependent nonlinear damping in nonlinear vibrations of rectangular plates. The solution of the nonlinear vibration problems is obtained through Lagrange equations by deriving the potential energy of the plate and the dissipated energy, both geometrically nonlinear and frequency-dependent. The model is then applied to a silicone rubber rectangular plate tested experimentally. The plate was glued to a metal frame and harmonically excited by stepped sine testing at different force levels and the vibration response was measured by a laser Doppler vibrometer. The comparison of numerical and experimental results was satisfactorily carried out for: (i) nonlinear vibration responses in the frequency and time domain at different excitation levels, (ii) dissipated energy versus excitation frequency and excitation force, (iii) storage energy and (iv) loss factor, which is particularly interesting to evaluate the plate dissipation versus frequency at different excitation levels. Finally, the linear and nonlinear damping terms are compared.