Tadeusz Stepinski

Efficient tool for designing 2D phased arrays in lamb waves imaging of isotropic structures

Ultrasonic phased arrays have a considerable application potential for structural health monitoring (SHM) of planar structures. 2D topologies are required to obtain unequivocal damage localization in these applications. Since array performance depends, among other factors, on its topology, there is a demand for robust and numerically efficient tools for arrays design. To deal with this problem we propose a method based on frequency-dependent structure transfer function that can deal with multi-modal and dispersive nature of Lamb waves as well as with the arbitrary shape of the excitation bursts. The proposed method is validated using an accurate numerical model of waves propagation. Finally, an efficient experimental method is proposed employing virtual array implemented by means of scanning laser vibrometer for sensing the Lamb waves in multiple points corresponding to the locations of the 2D array elements. In this way the performance of various array topologies can be evaluated experimentally in the reception mode without the need for a physical prototype.

Experimental comparison of 2D arrays topologies for SHM of planar structures

In this paper we present a new methodology for theoretical, numerical and experimental investigations of various 2D arrays topologies. The theoretical evaluation is performed using frequency-dependent structure transfer function that affects propagation of Lamb waves (LWs) through the dispersive medium and enables investigation of the arrays performance for a defined excitation signal. The numerical simulations are conducted using local interaction simulation approach (LISA) implemented on the NVIDIA R CUDA R graphical processing unit (GPU), which considerably accelerates 3D simulations of LWs propagation in a short time period. Finally, scanning laser vibrometer is used to sense the LWs excited by PZT transducers, in multiple points corresponding to the locations of the 2D array elements. In this way performance of various array architectures in the reception mode can be evaluated experimentally without the need of physical prototype - a change of topology requires only straightforward modification of the measurement points distribution at the tested plate.

Separation of Lamb waves modes using polarization filter of 3D laser measured signals

Interpretation of Lamb waves signals can rise serious difficulties due to their multi-modal nature. Different modes propagating with different velocities can be misleading with damage reflected components. As a solution to this problem we propose a technique capable of modes separation based on a polarization filter. Both S0 and A0 Lamb modes exhibit elliptical polarization, however, their polarization parameters, i.e. the ratios of in-plane and out-of-plane displacements and phase-shifts between these components are different. Furthermore, these parameters can be considered constant in a narrow frequency band. Therefore, if the vertical and horizontal components of the wave motion are available, it is possible to apply signal processing technique referred to as oblique polarization filter. This operation is based on phase-shifts and amplifications of the in- and out-of-plane components, which results in orthogonal, linearly polarized A0 and S0 waves signals. In this paper the proposed technique will be illustrated using both numerical simulations and experimental data. The simulations of wave propagation were performed using local interaction simulation approach (LISA) assuming isotropic material. The experiments were performed using 3D laser scanning Doppler vibrometer that allowed to capture the in-plane and out-of-plane wave components.

Interdigital Transducers in Structural Health Monitoring Based on Lamb Waves - A State of the Art

IDTs have the potential of increasing the versatility of SHM systems by their multiple capabilities. Migration of the IDT technology in SHM systems and devices is reviewed in this paper. A summary review of different types of IDTs is presented and their salient features are presented in terms of applicability in the Lamb wave based SHM systems. Comprehensive review is provided concerning the implementation of IDT capabilities towards the development of SHM systems. Experimental results obtained with prototype IDTs are provided for illustration. Finally, future development directions of the IDTs dedicated to SHM systems are outlined.

Data fusion for compensation of temperature variations in Lamb-wave based SHM systems

Temperature variations affect Lamb wave propagation and therefore in this way they can severely limit application of baseline signals in SHM systems. Various techniques are proposed in the paper to solve this problem. New method based on an interpretation of multiple signals acquired in distinct points of the structure is introduced and compared with other widely used approaches. Data fusion is used to merge a number of methods into one with a substantially increased efficiency.

Application of artificial neural networks for damage indices classification with the use of Lamb waves for the aerospace structures

Lamb waves (LW) are used for damage detection and health monitoring due to the long range propagation ability and sensitivity to structural integrity changes as well as their robustness in different applications. However, due to the dispersive character and multimode nature of LWs, analysis of the acquired ultrasonic signals is very complex. It becomes even more difficult when applied to a complex structure, for instance, an aircraft component with riveted joints and stringers characterized by difficult geometries. Therefore, numerous approaches to the evaluation of damage indices have been proposed in the literature. In this paper, comparison a number of damage indices applied to LWs testing in aircraft aluminum panels. The damage indices, known from the literature have been selected from the application point of view. Artificial neural network has been used for the classification of fatigue cracks and artificial damages induced in the specimens taken from a real aircraft structure. Article presents results of simulation, data analysis and data classification obtained using selected and dedicated neural network. The main aim of the presented research was to develop signal processing and signal classification methods for an aircraft health monitoring system. The article presents a part of the research carried out in the project named SYMOST.

Development of Lamb Waves-Based SHM Systems

Guided waves (GW) based methods are a promising tool for structural health monitoring (SHM) of plate-like metallic and composite structures in which high safety standards are required. In this paper we present research with the aim to design and manufacture a prototype of Lamb waves (LW) SHM system. Two approaches can be applied for SHM of plate-like structures. One of them can be based on a sparse array and damage imaging involving incoherent summation of signals envelope. The second approach involves phased arrays with transducers spaced at a distance lower than half wavelength of the excited Lamb-mode. The influence of an arrays parameters on beamforming of Lamb waves is discussed in the case of linear array. It appears that an unequivocal localization of damage on a plate requires a 2D arrays topology; therefore a star-shaped active array was designed and manufactured for the developed SHM system. Two signal processing approaches were applied for that array, the standard one, based on the delay and sum (DAS) synthetic aperture focusing scheme, and the second one, using a self-focusing technique to obtain the separate images for each scatterer existing in the plate.

Artificial neural network ensembles for fatigue damage detection in aircraft

Neural networks are commonly recognized tools for the classification of multidimensional data obtained in structural health monitoring (SHM) systems. Their configuration for a given scenario is, however, a challenging task, which limits the possibilities of their practical applications. In this article the authors propose using the neural network ensemble approach for the classification of SHM data generated by guided wave sensor networks. The overproduce and choose strategy is used for designing ensembles containing different types and sizes of neural networks. The proposed method allows for a significant increase of the state assessment reliability, which is illustrated by the results obtained from the practical industrial case of a full-scale aircraft test. The method is verified in the process of detecting fatigue cracks propagating in the aircraft load-carrying structure. The long-term experiments are performed in variable environmental conditions with a net of structure-embedded piezoelectric sensors.

Tunable interdigital transducers made of piezoelectric macro-fiber composite

The number of applications of Lamb waves (LWs) based structural health monitoring (SHM) has significantly increased in recent decades. The growth of interest results from several advantages of this diagnostic technique, that is, considerable mode selectivity and directivity that allow for the assessment of the technical condition of a monitored structure. Successful applications of LWs in the field of SHM stimulate continuous improvement of the transducers design to enable capturing more reliable diagnostic data. The paper introduces a new type of transducer that may be used in the LWs based SHM systems, namely tunable-interdigital transducer (T-IDT) based on macro-fiber composites (MFC). The authors provide a short overview on different types of transducers that may be used in SHM applications, followed by a detailed description of the structure of proposed T-IDT. Finally, the results of numerical and experimental tests carried out employing the proposed transducer are discussed and compared to those obtained with a traditional IDT.

Remote Monitoring of Fatigue Cracks Growth in the Aircraft Structure Based on Active Piezosensor Network during the Full Scale Fatigue Test

One of the major issues from a structural integrity point of view of the aircraft structure is an appropriate health monitoring technology delivery for the damage tolerant philosophy. This paper presents a development of a system for fatigue crack growth monitoring and early damage detection in the PZL 130 ORLIK TC II turbo-prop military trainer aft structure. The maintenance system of the aircraft shifts from the safe-life to the hard-time. The aircraft started Full Scale Fatigue Test (FSFT) which will continue up to 2013. In the article a built block approach for the system design, signal modeling, sensing and signal processing as well as damage detection is presented. Taking into the consideration a previous experience of AGH as well as AFIT, a network of PZT transducers was deployed in the aircraft structure hot-spots. The system components are: remote monitoring unit, signal analysis, graphical user interface, sensor self-diagnostic tools, and data classification model. Description of damage detection capabilities are delivered in the paper. In particular some issues concerning the proposed damage indices and its application to crack growth estimation models are discussed. Fishers Linear Discriminant is used as a method to obtain effective crack growth predictors and one of the self-diagnostic tools used in the system. The results of the data collected from specimen fatigue tests are delivered and cross-validation technique is used to evaluate a classification model based on the damage indices derived.