S.G. Pierce

Broadband Lamb wave measurements in aluminium and carbon/glass fibre reinforced composite materials using non-contacting laser generation and detection

Abstract Broadband measurements of Lamb wave dispersion characteristics have been performed in aluminium, carbon and carbon/glass fibre hybrid composite materials using a non-contacting optical technique. A high powered Q-switched Nd:YAG laser was used to initiate the Lamb wave spectrum in the materials, and an optical fibre Michelson interferometer was used to monitor the outof-plane displacements associated with the propagating modes. Comparison of experimental results with theoretical modelling in both the aluminium and composite samples indicated good agreement for the excited modes. The application of this technique to the non-destructive testing and elastic property measurement of composite materials is discussed.

Features for damage detection with insensitivity to environmental and operational variations

This paper explores and compares the application of three different approaches to the data normalization problem in structural health monitoring (SHM), which concerns the removal of confounding trends induced by varying operational conditions from a measured structural response that correlates with damage. The methodologies for singling out or creating damage-sensitive features that are insensitive to environmental influences explored here include cointegration, outlier analysis and an approach relying on principal component analysis. The application of cointegration is a new idea for SHM from the field of econometrics, and this is the first work in which it has been comprehensively applied to an SHM problem. Results when applying cointegration are compared with results from the more familiar outlier analysis and an approach that uses minor principal components. The ability of these methods for removing the effects of environmental/operational variations from damage-sensitive features is demonstrated and compared with benchmark data from the Brite-Euram project DAMASCOS (BE97 4213), which was collected from a Lamb-wave inspection of a composite panel subject to temperature variations in an environmental chamber.

Surface-bonded and embedded optical fibers as ultrasonic sensors

The effectiveness of surface-bonded and embedded optical fibers for the detection of ultrasonic Lamb waves in 2-3-mm-thick steel, carbon-fiber-reinforced plastic (CFRP) and glass-reinforced plastic (GRP) plates are compared. A novel integrating ultrasonic sensor was achieved using the signal arm of an actively stabilized 633-nm homodyne Mach-Zehnder fiber interferometer which was either bonded directly to the plate surface or spliced to single-mode fibers embedded within a composite plate during manufacture. An embedded fiber is shown to be about 20 times more sensitive to Lamb wave motions than a surface-bonded fiber. However, the latter may be more practical.

Detection of defects in composite plates using Lamb waves and novelty detection

The problem of detecting damage in composite plates is addressed here using L amb waves and novelty detection. Damage can be inferred from the scattering and modification of the Lamb wavefield as it passes through a defect. In order to produce an automatic diagnostic tool which can operate on measured time data, the method of novelty detection is used. This depends on establishing a description of normality which then allows subsequent signals to be flagged as anomalous if they deviate from normal condition. Three methods of novelty detection are illustrated: two statistical methods and one neural. The methods are demonstrated on experimental data captured from two composite plates.

Surface-bonded optical fibre sensors for the inspection of CFRP plates using ultrasonic Lamb waves

Surface-bonded single-mode optical fibre sensors have been used to monitor the interaction of ultrasonic Lamb waves with defects in carbon fibre composite plates. Lamb waves were initiated using Perspex-coupled piezoelectric transducers. The defects investigated comprised holes, regions of impact damage and delaminations. Holes could be identified by analysing direct reflections and impact damage by back-wall echo amplitude. Large delaminations gave a poor direct reflection. Evidence was found for mode conversion at centre plane delaminations.

Generation and reception of ultrasonic guided waves in composite plates using conformable piezoelectric transmitters and optical-fiber detectors

A condition monitoring nondestructive evaluation (NDE) system, combining the generation of ultrasonic Lamb waves in thin composite plates and their subsequent detection using an embedded optical fiber system is described. The acoustic source is of low profile with respect to the composite plate thickness, surface conformable, and able to efficiently launch a known Lamb wave mode, at operating frequencies between 100 and 500 kHz, over typical propagation distances of 100 to 500 mm. It incorporates both piezocomposite technology and interdigital design techniques to generate the fundamental symmetrical Lamb wave mode in both metallic and carbon-fiber composite plates. Linear systems and finite element modeling techniques have been used to evaluate the operation of the transducer structure, and this is supplemented by experimental verification of the simulated data. An optical fiber, either bonded to the surface or embedded across the length of the composite plate samples, is used to detect the propagating ultrasonic Lamb waves. Single mode silica fiber has been used in conjunction with a portable 633 nm Mach-Zehnder interferometer for signal demodulation and subsequent data acquisition. This hybrid system is shown to generate and detect the fundamental symmetrical Lamb wave (s/sub 0/) in both carbon-fiber and glass-fiber reinforced composite plates. Importantly, the system signal-to-noise ratio (SNR) associated with the acoustic source compares favorably with s/sub 0/ Lamb wave generation using a conventional transducer and angled perspex wedge arrangement.

Time-of-flight measurement techniques for airborne ultrasonic ranging

Airborne ultrasonic ranging is used in a variety of different engineering applications for which other positional metrology techniques cannot be used, for example in closed-cell locations, when optical line of sight is limited, and when multipath effects preclude electromagnetic-based wireless systems. Although subject to fundamental physical limitations, e.g., because of the temperature dependence of acoustic velocity in air, these acoustic techniques often provide a cost-effective solution for applications in mobile robotics, structural inspection, and biomedical imaging. In this article, the different techniques and limitations of a range of airborne ultrasonic ranging approaches are reviewed, with an emphasis on the accuracy and repeatability of the measurements. Simple time-domain approaches are compared with their frequency-domain equivalents, and the use of hybrid models and biologically inspired approaches are discussed.

A Noncontact Ultrasonic Platform for Structural Inspection

Miniature robotic vehicles are receiving increasing attention for use in nondestructive testing (NDE) due to their attractiveness in terms of cost, safety, and their accessibility to areas where manual inspection is not practical. Conventional ultrasonic inspection requires the provision of a suitable coupling liquid between the probe and the structure under test. This necessitates either an on board reservoir or umbilical providing a constant flow of coupling fluid, neither of which are practical for a fleet of miniature robotic inspection vehicles. Air-coupled ultrasound offers the possibility of couplant-free ultrasonic inspection. This paper describes the sensing methodology, hardware platform and algorithms used to integrate an air-coupled ultrasonic inspection payload into a miniature robotic vehicle platform. The work takes account of the robots inherent positional uncertainty when constructing an image of the test specimen from aggregated sensor measurements. This paper concludes with the results of an automatic inspection of a aluminium sample.

Evaluation of Neural Network Robust Reliability Using Information-Gap Theory

A novel technique for the evaluation of neural network robustness against uncertainty using a nonprobabilistic approach is presented. Conventional optimization techniques were employed to train multilayer perceptron (MLP) networks, which were then probed with an uncertainty analysis using an information-gap model to quantify the network response to uncertainty in the input data. It is demonstrated that the best performing network on data with low uncertainty is not in general the optimal network on data with a higher degree of input uncertainty. Using the concepts of information-gap theory, this paper develops a theoretical framework for information-gap uncertainty applied to neural networks, and explores the practical application of the procedure to three sample cases. The first consists of a simple two-dimensional (2-D) classification network operating on a known Gaussian distribution, the second a nine-lass vibration classification problem from an aircraft wing, and the third a two-class example from a database of breast cancer incidence

Miniature Mobile Sensor Platforms for Condition Monitoring of Structures

In this paper, a wireless, multisensor inspection system for nondestructive evaluation (NDE) of materials is described. The sensor configuration enables two inspection modes-magnetic (flux leakage and eddy current) and noncontact ultrasound. Each is designed to function in a complementary manner, maximizing the potential for detection of both surface and internal defects. Particular emphasis is placed on the generic architecture of a novel, intelligent sensor platform, and its positioning on the structure under test. The sensor units are capable of wireless communication with a remote host computer, which controls manipulation and data interpretation. Results are presented in the form of automatic scans with different NDE sensors in a series of experiments on thin plate structures. To highlight the advantage of utilizing multiple inspection modalities, data fusion approaches are employed to combine data collected by complementary sensor systems. Fusion of data is shown to demonstrate the potential for improved inspection reliability.