Jeannette R. Wait

Wavelet-based active sensing for delamination detection in composite structures

In this paper a signal processing technique is developed to detect delamination on composite structures. In particular, a wavelet-based signal processing technique is developed and combined with an active sensing system to produce a near-real-time, online monitoring system for composite structures. A layer of piezoelectric patches is used to generate an input signal with a specific wavelet waveform and to measure response signals. Then, the response signals are processed by a wavelet transform to extract damage-sensitive features from the original signals. The applicability of the proposed method to delamination identification has been demonstrated by experimental studies of a composite plate under varying temperature and boundary conditions.

Structural Health Monitoring Using Modular Wireless Sensors

System integration of an online structural health monitoring module was accomplished by coupling commercially available microelectro-mechanical system sensors and a wireless telemetry unit with damage detection firmware. To showcase the capabilities of the integrated monitoring module, a bolted frame structure was constructed, and the preload in one of the bolted joints was controlled by a piezoelectric stack actuator to simulate gradual deterioration of a bolted connection. Two separate damage detection algorithms were used to classify a joint as damaged or undamaged. First, a statistical process control algorithm was used to monitor the correlation of vibration data from two accelerometers mounted across a joint. Changes in correlation were used to detect damage to the joint. For each joint, data were processed locally on a microprocessor integrated with the wireless module, and the diagnosis result was remotely transmitted to the base monitoring station. Second, a more sophisticated damage detection algorithm combining time series analysis and statistical hypothesis testing was employed using a conventional wired data acquisition system to classify a joint on the demonstration structure as damaged or undamaged.

Using state space predictive modeling with chaotic interrogation in detecting joint preload loss in a frame structure experiment

This work explores the role of steady-state dynamic analysis in the vibration-based structural health monitoring field. While more traditional approaches focus on transient or stochastic vibration analysis, the method described here utilizes a geometric portrait of system dynamics to extract information about the steady-state response of the structure to sustained excitation. The approach utilizes the fundamental properties of chaotic signals to produce low-dimensional response data which are then analyzed for features which indicate the degree to which the dynamics have been altered by damage. A discussion of the fundamental issues involved in the approach is presented along with experimental evidence of the approachs ability to discriminate among several damage scenarios.

Integrated Structural Health Assessment Using Piezoelectric Active Sensors

This paper illustrates an integrated approach for identifying structural damage. The method presented utilizes piezoelectric (PZT) materials to actuate/sense the dynamic response of the structures. Two damage identification techniques are integrated in this study, including impedance methods and Lamb wave propagations. The impedance method monitors the variations in structural mechanical impedance, which is coupled with the electrical impedance of the PZT patch. In Lamb wave propagations, one PZT patch acting as an actuator launches an elastic wave through the structure, and responses are measured by an array of PZT sensors. The changes in both wave attenuation and reflection are used to detect and locate the damage. Both the Lamb wave and impedance methods operate in high frequency ranges at which there are measurable changes in structural responses even for incipient damage such as small cracks, debonding, or loose connections. The combination of the local impedance method with the wave propagation based approach allows a better characterization of the system’s structural integrity. The paper concludes with experimental results to demonstrate the feasibility of this integrated active sensing technology.

Plate damage identification using wave propagation and impedance methods

This paper illustrates an integrated approach for identifying structural damage in an aluminum plate. Piezoelectric (PZT) materials are used to actuate/sense the dynamic response of the structure. Two damage identification techniques are integrated in this study, including Lamb wave propagations and impedance methods. In Lamb wave propagations, one PZT launches an elastic wave through the structure, and responses are measured by an array of PZT sensors. The changes in both wave attenuation and reflection are used to detect and locate the damage. The impedance method monitors the variations in structural mechanical impedance, which is coupled with the electrical impedance of the PZT. Both methods operate in high frequency ranges at which there are measurable changes in structural responses even for incipient damage such as small cracks or loose connections. This paper summarizes two methods used for damage identification, experimental procedures, and additional issues that can be used as a guideline for future investigations.

Dynamical Assessment of Structural Damage Using the Continuity Statistic

Recent works by Nichols et al. (Nichols, J.M., Todd, M.D., Seaver, M. and Virgin, L.N. (2003). Use of chaotic excitation and attractor property analysis in structural health monitoring. Phys Rev E, 67(016209)) and Pecora et al. (Todd, M.D., Nichols, J.M., Pecora, L.M. and Virgin, L.N. (2001). Vibration-based damage assessment utilizing state-space geometry changes: Local attractor variance ratio. Smart Materials and Structures, 10, 1000-1008.) have shown that steady-state dynamic analysis of structural health exhibits advantages over transient vibrational analysis. A geometric representation of system dynamics can be used to extract information about a structure’s response to sustained excitation. Analysis of various features of the geometric representation can be used to describe the degree to which the dynamics have been altered by damage. Here, the feature we employ is the ‘‘continuity test,’’ a statistical test first described by Pecora et al. (Pecora, L.M., Carroll, T.L. and Heagy, J.F. (1997). Statistics for continuity and differentiability: an application to attractor reconstruction from time-series. Fields Institute Communications, 11). This test measures the probability that a continuous function exists from one geometric object to another. In this implementation, we formulate a new null hypothesis which serves to make the test less sensitive to noise in the data than the original test. Using experimental data from an excited three-story aluminum frame structure with multiple sensors at the joints, we show that the continuity test can be used not only to detect, but also in some cases to localize damage to particular joints in the frame structure.

High-Frequency Response Functions for Composite Plate Monitoring with Ultrasonic Validation

In this study, frequency response functions (FRF) measured by piezoelectric Macro-Fiber Composite (MFC) actuators/sensors are used to detect subsurface delamination in a composite plate. The plate is impacted to seed damage in the form of ply delamination. Then, the MFCbased active-sensing system exerts an excitation into the plate, and measures the subsequent responses. Traditional piezoceramic materials are also mounted in comparable locations on the plate to compare their performances. FRF and damage indicator features are derived from the measured signals and used to assess the condition of the plate. Validation of the delamination is completed using an ultrasonic C-scan method. The effective area of observed damage is well correlated to the damage indicator feature.

The Use of Frequency Response Functions for Composite Plate Monitoring With Ultrasonic Validations

In this study, frequency response functions (FRF) measured by piezoelectric Macro-Fiber Composites (MFC) are used to detect invisible delamination in a composite plate. The plate is impacted to seed damage in the form of fiber delamination. Then, the active-sensing system exerts an excitation into the plate, and measures the subsequent responses. FRF and damage indicator features are derived from the measured signals and used to assess the condition of the plate. Validation of the delamination is completed using an ultrasonic scan method. The effective area of observed damage is well correlated to the damage indicator feature.Copyright