Martin P. DeSimio

Automated detection of delamination and disbond from wavefield images obtained using a scanning laser vibrometer

The paper presents signal and image processing algorithms to automatically detect delamination and disbond in composite plates from wavefield images obtained using a scanning laser Doppler vibrometer (LDV). Lamb waves are excited by a lead zirconate titanate transducer (PZT) mounted on the surface of a composite plate, and the out-of-plane velocity field is measured using an LDV. From the scanned time signals, wavefield images are constructed and processed to study the interaction of Lamb waves with hidden delaminations and disbonds. In particular, the frequency–wavenumber (f–k) domain filter and the Laplacian image filter are used to enhance the visibility of defects in the scanned images. Thereafter, a statistical cluster detection algorithm is used to identify the defect location and distinguish damaged specimens from undamaged ones.

Impact localization in complex structures using laser-based time reversal:

This study presents a new impact localization technique that can pinpoint the location of an impact event within a complex structure using a time-reversal concept, surface-mounted piezoelectric transducers, and a scanning laser Doppler vibrometer. First, an impulse response function between an impact location and a piezoelectric transducer is approximated by exciting the piezoelectric transducer instead and measuring the response at the impact location using scanning laser Doppler vibrometer. Then, training impulse response functions are assembled by repeating this process for various potential impact locations and piezoelectric transducers. Once an actual impact event occurs, the impact response is recorded by the piezoelectric transducers and compared with the training impulse response functions. The correlations between the impact response and the impulse response functions in the training data are computed using a unique concept of time reversal. Finally, the training impulse response function, which gives the maximum correlation, is chosen from the training data set and the impact location is identified. The proposed impact localization technique has the following advantages over the existing techniques: (a) it can be applied to isotropic/anisotropic plate structures with additional complex features such as stringers, stiffeners, spars, and rivet connections; (b) only simple correlation calculation based on time reversal is required, making it attractive for real-time automated monitoring; and (c) training is conducted using noncontact scanning laser Doppler vibrometer and the existing piezoelectric transducers that may already be installed for other structural health–monitoring applications. Impact events on an actual composite aircraft wing and an actual aluminum fuselage are successfully identified using the proposed technique.

Lamb Wave Propagation in Varying Isothermal Environments

Military and commercial aerospace organizations are exploring structural health monitoring (SHM) systems to reduce maintenance costs and to verify the integrity of structural components exposed to harsh conditions. This technical note considers the use of Lamb waves to monitor plate and shell components of aerospace structures. For fielded applications, SHM systems will need to operate across a variety of environmental conditions, including large temperature ranges. Therefore, it is critical to understand the effects of temperature on Lamb wave propagation. The focus of this study is the effect of temperature on Lamb wave propagation in a constant-thickness metallic plate under isothermal conditions. Experimental measurements and analytical predictions are made over temperatures ranging from -18°C to 107°C. Results indicate that only small and predictable changes in the wave propagation behavior occur over the temperature range investigated. This is significant because it may allow SHM systems to be designed for aircraft systems operating within this range without the need for complex compensation techniques.

Fastener Damage Estimation in a Square Aluminum Plate

To reduce costs and meet turn-around goals of future space vehicles, structural health monitoring systems are needed to assess the health of the entire vehicle structure within hours of the completed mission. In particular, the thermal protection system must be in good condition before launch due to its critical role in protecting the vehicle’s primary structure and subsystems. The capability to detect fastener failure is critical, as the overall thermal protection system for a vehicle will likely include a number of adjacent panels that are mechanically fastened to the substructure. This article discusses experimental and analytical efforts focused on estimating fastener damage in a square aluminum plate test article. Fastener condition is estimated using classifiers based on statistical pattern recognition methods. The classifiers utilize features from measured vibration data with the ability to discriminate between damage conditions. Finite element analyses are used to provide a physical understanding of the structural dynamics of the aluminum plate and an interpretation of the selected features used for the classifier. Techniques to detect, locate, and assess damage resulting due to fastener failure have been investigated. The classification systems presented perform reasonably well in detecting and localizing damage, particularly if the damage is fairly severe. However, the classification system performance is much worse at assessing the severity of damage, particularly for lower levels of damage.

A Comparison of 1D and 3D Laser Vibrometry Measurements of Lamb Waves

This paper compares and contrasts one-dimensional (1D) and three-dimensional (3D) scanning laser Doppler vibrometer (LDV) measurements of Lamb waves generated by lead zirconate titanate (PZT) transducers. Due to the large cost and capability differences between the previously mentioned systems, this study is provided to highlight differences between these systems. 1D measurements are defined here as measurements of only out-of-plane velocities which are well-suited for studying anti-symmetric Lamb wave modes. 3D measurements provide both in- and out-of-plane velocities, which are especially important when studying both symmetric and anti-symmetric Lamb wave modes. The primary reason for using scanning LDVs is that these systems can make non-contact, accurate surface velocity measurements over a spatially-dense grid providing relatively high resolution image sequences of wave propagation. These scans can result in a clear understanding of Lamb waves propagating in plate-like structures and interacting with structural variations.

The probability of detection for structural health monitoring systems: Repeated measures data

The United States Air Force currently relies on schedule-based inspections using nondestructive evaluation methods for ensuring airframe integrity. The sensitivity of a nondestructive evaluation method is quantified statistically using a probability of detection process. The purpose of the probability of detection process is to generate a a 90 | 95 metric for a given nondestructive evaluation technique and corresponding defect (e.g. crack). This process could be conducted under various inspection conditions and defect sizes. The set of factors varied in the process is controlled to allow each nondestructive evaluation inspection to be treated as statistically independent. Current United States Air Force structural inspections are performed at time intervals that adhere to the independence assumption. However, the United States Air Force plans to service airframes based on their actual condition instead of the current schedule-based approach. Accordingly, there is emphasis on developing advanced health management technologies, such as structural health monitoring systems, which provide an automated and real-time assessment of a structure’s ability to serve its intended purpose. Therefore, structural health monitoring is considered to be equivalent to an in situ nondestructive evaluation structural inspection device. With a structural health monitoring system, the time interval between inspections will be much smaller than the time intervals between nondestructive evaluation inspections. Since structural health monitoring measurements are from the same sensors, in the same location, the independent measurement assumption used to analyze nondestructive evaluation methods is invalid. In this article, we present a statistical method consistent with current probability of detection process, yet designed to appropriately analyze dependent data. We demonstrate this method first with simulated data and then with experimental data from three test specimens of a representative aircraft structural component. This method leverages the advantages of a structural health monitoring system through its frequent measurements while maintaining its usefulness through appropriately computed probability of detection values. Furthermore, we present a numerical method for estimating the number of test specimens needed to achieve a desired a 90 | 95 value.

Computational Lamb wave model validation using 1D and 3D laser vibrometer measurements

Lamb waves are being explored for structural health monitoring (SHM) due to their capability of detecting relatively small damage within reasonably large inspection areas. However, Lamb wave behavior is fairly complex, and therefore, various computational techniques, including finite element analysis (FEA), have been utilized to design appropriate SHM systems. Validation of these computational models is often based on a limited number of measurements made at discrete locations on the structure. For example, models of pitch-catch of Lamb waves may be validated by comparing predicted waveform time histories at a sensor to experimentally measured results. The use of laser Doppler vibrometer (LDV) measurements offers the potential to improve model validation. One-dimensional (1D) LDV scans provide detailed out-of-plane measurements over the entire scanned region, and checks at discrete sensor locations can still be performed. The use of three-dimensional (3D) laser vibrometer scans further expands the data available for correlation by providing in- and out-of-plane velocity components over the entire scanned region. This paper compares the use of 1D and 3D laser vibrometer data for qualitatively and quantitatively validating models of healthy metallic and composite plates.

Beam Forming of Lamb Waves for Structural Health Monitoring

Structural health monitoring techniques are being developed to reduce operations and support costs, increase availability, and maintain safety of current and future air vehicle systems. The use of Lamb waves, guided elastic waves in a plate, has shown promise in detecting localized damage, such as cracking or corrosion, due to the short wavelengths of the propagating waves. Lamb wave techniques have been utilized for structural health monitoring of simple plate and shell structures. However, most aerospace structures are significantly more complex and advanced techniques may be required. One advanced technique involves using an array of piezoelectric transducers to generate or sense elastic waves in the structure under inspection. By adjusting the spacing and/or phasing between the piezoelectric transducers, transmitted or received waves can be focused in a specific direction. This paper presents beam forming details based on analytical modeling, using the finite element method, and experimental testing, using an array of piezoelectric transducers on an aluminum panel. Results are shown to compare well to theoretical predictions.

Delamination Detection in Composite Structures using Laser Vibrometer Measurement of Lamb Waves

In this study, the feasibility of using a scanning laser vibrometer for detecting hidden delamination in multi-layer composites is explored. First, Lamb waves are excited by Lead Zirconate Titanate (PZT) transducers mounted on the surface of a composite plate, and the out-of-plane ultrasonic velocity field is measured using a 1D scanning laser vibrometer. From the scanned time signals, wave field images are constructed and processed to study the interaction of Lamb waves with hidden delamination. In order to highlight the defect area in the image, the performance of different image processing tools were investigated. In particular, the Laplacian image filter was found to accentuate the visual indications of the ultrasound-defect interaction by suppressing the presence of incident waves in the wave field images. The performance of the proposed scheme is investigated using experimental data collected from a 1.8 mm thick multilayer composite plate and a 10 mm thick composite wing structure.

Impact localization in an aircraft fuselage using laser based time reversal

This study presents a new impact localization technique that can pinpoint the location of an impact event within a complex aircraft fuselage using a time reversal concept and a scanning laser Doppler vibrometer (SLDV). First, an impulse response function (IRF) between an impact location and a sensing piezoelectric transducer is approximated by exciting the sensing piezoelectric transducer instead and measuring the response at the impact location using SLDV. Then, training IRFs are assembled by repeating this process for various potential impact locations and sensing piezoelectric transducers. Once an actual impact event occurs, the impact response is recorded and compared with the training IRFs. The correlations between the impact response and the IRFs in the training data are computed using a unique concept of time reversal. Finally, the training IRF, which gives the maximum correlation, is chosen from the training data set, and the impact location is identified. The proposed impact technique has the following advantages over the existing techniques: (1) it can be applied to isotropic/anisotropic plate structures with additional complex features such as stringers, stiffeners, spars and rivet connections; (2) only simple correlation calculation based on unique time reversal is required, making it attractive for real-time automated monitoring; (3) temperature variation barely affects the localization performance; and, (4) training is conducted using non-contact SLDV and the existing piezoelectric transducers which may already be installed for other structural health monitoring purposes. Impact events on an actual aluminum fuselage specimen are successfully identified using the proposed technique.