Ultrasonic Damage Detection Research Articles

Ultrasonic damage detection in lithium-ion cells with localized thermal abuse histories

Electric vehicles require nearly 1000 individual lithium-ion batteries to provide appropriate power and capacity. It has recently been shown that ultrasonic inspection can detect localized heating in a LIB cell with a combination of input frequencies and propagation paths [J. Acoust. Soc. Am. 152, A283 (2022)]. However, monitoring the thermal conditions of every cell in a battery pack is highly challenging to implement. This work explores the use of ultrasonic inspection to diagnose LIB cells with damage histories due to local, thermal abuse. LIBs were interrogated with ultrasonic waves while subjected to electrical and thermal loading, specifically, standard charge-dischargecycling followed by moderate localized thermal abuse and another phase of charge-discharge cycling. Ultrasonic signals from each portion of the test and data for the cycling before and after heating are directly compared for indicators of past abuse. Experimental data are compared to a transfer-matrix model to simulate the time-of-flight (TOF) through an individual cell using temperature-specific material properties for individual components to simulate the effect of heat on TOF. Experimental results indicate that deviations in time-domain features of the received signals can be used to detect previous thermal abuse via ultrasonic testing during charge-discharge cycling after thermal abuse.

Ultrasonic damage detection in lithium-ion batteries subjected to localized heating

The transition from internal combustion to electrically powered vehicles (EVs) is accelerating, with some estimates predicting that 45% of new cars sold in the US will be fully electric by 2035. EVs will be powered by lithium-ion batteries (LIBs). This high-power application can subject LIBs to significant electrical, mechanical, and thermal abuse. Predicting and preventing thermal runaway (TR) is therefore of utmost importance to save lives and ameliorate the transition to renewable energy. Currently, battery management systems monitor cell voltage, current, temperature, and presence of gases, which does not provide sufficient advanced warning of a catastrophic event [J. Acoust. Soc. Am., 150, A66 (2021)]. This work explores the viability of evaluating cell safety by monitoring and interpreting ultrasonic signals propagating through a battery as it undergoes localized heating. We monitor different portions of received waveforms, linking them to specific propagating modes or multi-path arrivals. A finite element model is then used to understand the mode of propagation of the chosen frequencies, and the methodology is applied to both 10Ah and 60Ah cells. The time-domain features of signal amplitude and time-of-flight are used to create safety metrics which warn of TR as much as 25 min in advance of failure.

Comparison of sensitivity in nonlinear ultrasonic detection based on Lamb wave phase velocity matching mode

ABSTRACT In nonlinear ultrasonic damage detection, the appropriate Lamb wave mode to accurately characterise the nonlinearity attributed to the material damage should be selected important. However, an effective mode is more difficult to select practically as impacted by the dispersion and multi-mode characteristic of the Lamb wave. In this study, based on the dispersion curve of Lamb waves, the modes meeting the second harmonics and third harmonics phase velocity matching were given, and the nonlinear cumulative effects exerted by different modes on fatigue cracks were compared. In addition, an investigation was conducted on the amplitude change of the second and third harmonics signal of the identical fatigue damage. The results show that the harmonic amplitude decreases with the increase of the fatigue crack length. The third harmonics under the two modes are more sensitive to fatigue damage than the second harmonics. Moreover, the amplitude of the third harmonic excited by S1 mode exceeds that of the other mode. As the fatigue crack length increases, the relative second- and third-order nonlinear coefficients generated by S1 mode have approximately the same trend, first increasing and then decreasing. The results reveal that the third harmonic under S1 mode could more effectively characterise fatigue damage.

3D-printed phononic crystal waveguide transducers for nonlinear ultrasonic damage detection

Nonlinear ultrasonic methods typically measure second harmonic waves for a rapid and sensitive detection of material micro-cracks. However, fictitious second harmonics generated by the ultrasonic equipment can interfere with signal measurements, causing poor damage detection. This paper aims at enhancing the damage sensitivity of nonlinear ultrasound by developing acrylic phononic crystal waveguide transducers using Polyjet additive manufacturing, which can filter out undesired nonlinear harmonic waves. These sensing devices consist of traditional piezoelectric sensors surface bonded on periodically corrugated structures. Such periodicity can induce stop band frequencies in which the propagation of ultrasonic waves is inhibited. Nonlinear ultrasonic tests confirmed the filtering capabilities of phononic crystal transducers to suppress harmonics created by the ultrasonic instrumentation, thus enabling second harmonic detection on a damage aluminium plate. These results pave the way for simpler, automatable and more accurate nonlinear ultrasonic inspection systems.

Ultrasonic Damage Detection of Impacted Long and Short Fibre Composite Specimens

Composite materials structures are particularly susceptible to the damages induced by low-velocity impacts that may result in Barely Visible Impact Damages (BVIDs), which can hardly be identified through visual inspection. These damages are particularly dangerous, since they can critically reduce the mechanical properties of the impacted structures. In this work, the damage induced in impacted long and short fibre composite specimens has been experimentally evaluated by means of Non-Destructive Technique (NDT) inspections. The damages size and location have been evaluated by means of ultrasonic testing to assess the influence of fibres aspect ratio (long and short fibres), fibres material (carbon and glass), volume fraction, and impact energy for low velocity impacts on composite specimens. Considerations about the failure mechanisms arising as a consequence of the impact event and their interactions have been finally introduced.

Laser ultrasonic damage detection in coating-substrate structure via Pearson correlation coefficient

This study explores the feasibility of using laser generated ultrasonic wave to detect the interfacial damage of coating-substrate structure. Two Pearson correlation coefficient based post processing algorithms are respectively modified and used in order to evaluate the damage-induced waveform variation and thus position the damage accurately. In addition, the ultrasonic signals of frequency-domain and time-domain are separately studied to optimize the damage visualization performance of the two approaches. The proposed method helps to facilitate nondestructive examination of laser ultrasonic technique.

A model based bayesian solution for characterization of complex damage scenarios in aerospace composite structures

Ultrasonic damage detection and characterization is commonly used in nondestructive evaluation (NDE) of aerospace composite components. In recent years there has been an increased development of guided wave based methods. In real materials and structures, these dispersive waves result in complicated behavior in the presence of complex damage scenarios. Model-based characterization methods utilize accurate three dimensional finite element models (FEMs) of guided wave interaction with realistic damage scenarios to aid in defect identification and classification. This work describes an inverse solution for realistic composite damage characterization by comparing the wavenumber-frequency spectra of experimental and simulated ultrasonic inspections. The composite laminate material properties are first verified through a Bayesian solution (Markov chain Monte Carlo), enabling uncertainty quantification surrounding the characterization. A study is undertaken to assess the efficacy of the proposed damage model and comparative metrics between the experimental and simulated output. The FEM is then parameterized with a damage model capable of describing the typical complex damage created by impact events in composites. The damage is characterized through a transdimensional Markov chain Monte Carlo solution, enabling a flexible damage model capable of adapting to the complex damage geometry investigated here. The posterior probability distributions of the individual delamination petals as well as the overall envelope of the damage site are determined.

Structural health monitoring feature design by genetic programming

Structural health monitoring (SHM) systems provide real-time damage and performance information for civil, aerospace, and other high-capital or life-safety critical structures. Conventional data processing involves pre-processing and extraction of low-dimensional features from in situ time series measurements. The features are then input to a statistical pattern recognition algorithm to perform the relevant classification or regression task necessary to facilitate decisions by the SHM system. Traditional design of signal processing and feature extraction algorithms can be an expensive and time-consuming process requiring extensive system knowledge and domain expertise. Genetic programming, a heuristic program search method from evolutionary computation, was recently adapted by the authors to perform automated, data-driven design of signal processing and feature extraction algorithms for statistical pattern recognition applications. The proposed method, called Autofead, is particularly suitable to handle the challenges inherent in algorithm design for SHM problems where the manifestation of damage in structural response measurements is often unclear or unknown. Autofead mines a training database of response measurements to discover information-rich features specific to the problem at hand. This study provides experimental validation on three SHM applications including ultrasonic damage detection, bearing damage classification for rotating machinery, and vibration-based structural health monitoring. Performance comparisons with common feature choices for each problem area are provided demonstrating the versatility of Autofead to produce significant algorithm improvements on a wide range of problems.

Guided waves in anisotropic and quasi-isotropic aerospace composites: Three-dimensional simulation and experiment

Three-dimensional (3D) elastic wave simulations can be used to investigate and optimize nondestructive evaluation (NDE) and structural health monitoring (SHM) ultrasonic damage detection techniques for aerospace materials. 3D anisotropic elastodynamic finite integration technique (EFIT) has been implemented for ultrasonic waves in carbon fiber reinforced polymer (CFRP) composite laminates. This paper describes 3D EFIT simulations of guided wave propagation in undamaged and damaged anisotropic and quasi-isotropic composite plates. Comparisons are made between simulations of guided waves in undamaged anisotropic composite plates and both experimental laser Doppler vibrometer (LDV) wavefield data and dispersion curves. Time domain and wavenumber domain comparisons are described. Wave interaction with complex geometry delamination damage is then simulated to investigate how simulation tools incorporating realistic damage geometries can aid in the understanding of wave interaction with CFRP damage. In order to move beyond simplistic assumptions of damage geometry, volumetric delamination data acquired via X-ray microfocus computed tomography is directly incorporated into the simulation. Simulated guided wave interaction with the complex geometry delamination is compared to experimental LDV time domain data and 3D wave interaction with the volumetric damage is discussed.

Approaches for ultrasonic damage detection in aircraft components for structural health monitoring.

Characterization of flaws is an important goal of ultrasonic NDE in aircraft components, especially to meet the new demands for structural health monitoring to achieve retirement for cause. This presentation describes approaches and results for two classes of damage: (1) impact damage in fiber-reinforced composites and (2) cracks in jet engine components. In the application of impact damage on composites the use of non-contact laser based ultrasound with a NdYAG laser as transmitter and Mach–Zehnder interferometer as receiver was complemented by acoustic microscopy. Results are described for both hard and soft impacts on a variety of composites. In the application of crack detection of jet engine components the main emphasis was on the development for in-situ high-temperature piezoelectric sensors. In particular, high temperature operation in excess of 1000 °C is described with sol-gel spray-on coatings, thin AlN films and single crystals of aluminum nitride. Some of the sensors are geared toward wireless retrieval of crack detection in turbine disks and blades. Whereas these approaches in ultrasonic NDE are not routine they hold high promise for near-future applications in the aerospace.