There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Staff members at Los Alamos National Laboratory (LANL) produced a summary of the structural health monitoring literature in 1995. This presentation will summarize the outcome of an updated review covering the years 1996 2001. The updated review follows the LANL statistical pattern recognition paradigm for SHM, which addresses four topics: 1. Operational Evaluation; 2. Data Acquisition and Cleansing; 3. Feature Extraction; and 4. Statistical Modeling for Feature Discrimination. The literature has been reviewed based on how a particular study addresses these four topics. A significant observation from this review is that although there are many more SHM studies being reported, the investigators, in general, have not yet fully embraced the well-developed tools from statistical pattern recognition. As such, the discrimination procedures employed are often lacking the appropriate rigor necessary for this technology to evolve beyond demonstration problems carried out in laboratory setting.

A review of structural health monitoring literature 1996-2001

A review of recent research on mechanics of multifunctional composite materials and structures

This study presents active sensing methods in structural health monitoring, for detecting cracks and debonds in metallic and composite structures, which can be potentially implemented into airframe structures. First, a pitch-catch method using a pair of piezoelectric actuator and sensor is introduced to generate a damage indeX which can be used to characterize damage at a known location. Tests on airbus fuselage panels are conducted to verify the method and damage indeX. The damage indeX relates changes in the energy content of a specific Lamb wave mode selected by group velocity analysis to the eXtent of damage. Second, an imaging method based on multiple pitch-catch information, a network of piezoelectric actuator/sensors, is presented for characterizing damage (location and size) without need for a structural or damage model. The imaging method with an autofocusing feature is applied to aluminum plates and a stiffened composite panel for method verification.

Pitch-catch Active Sensing Methods in Structural Health Monitoring for Aircraft Structures

Stimuli-responsive polymers (SRPs) are smart materials which can show noticeable changes in their properties with environmental stimulus variations. Novel functionalities can be delivered to textiles by integrating smart SRPs into them. SRPs inclusive of thermal-responsive polymers, moisture-responsive polymers, thermal-responsive hydrogels, pH-responsive hydrogels, and light-responsive polymers have been applied in textiles to improve or achieve textile smart functionalities. The functionalities include aesthetic appeal, comfort, textile soft display, smart controlled drug release, fantasy design with color changing, wound monitoring, smart wetting properties and protection against extreme variations in environmental conditions. In this review, the applications of SRPs in the textile and clothing sector are elucidated; the associated constraints in fabrication processes for textiles and their potential applications in the near future are discussed.

https://iopscience.iop.org/article/10.1088/0964-1726/21/5/053001/pdf

A review of stimuli-responsive polymers for smart textile applications

By implementing a built-in sensor network on a composite structure, crucial information regarding the condition, damage state, and service environment of the structure can be obtained. In this study, methods for integrating piezoelectric sensor networks into a composite structure during different fabrication processes, including the resin transfer molding (RTM) and filament winding processes, are examined. To integrate sensor networks with different contours of structures, the method to fabricate a three-dimensional (3-D) diagnostic layer is developed. It is demonstrated that a large number of sensors supported on a thin flexible dielectric film, called a SMART Layer, offers a simple and efficient way to integrate a large sensor network onto a complex 3-D structure. The sensor network permanently embedded inside the composite structures can be used with either active sensing or passive sensing to monitor the health condition of a structure throughout its lifetime.

Built-in sensor network for structural health monitoring of composite structure

Effect of adhesive on the performance of piezoelectric elements used to monitor structural health

An active diagnostic system using built-in piezoelectric actuator/sensor networks was developed for monitoring crack growth in a rocket engine pipe. The diagnostic system combines a sensor network, portable diagnostic hardware and data analysis software which allows for real-time in situ monitoring and long term tracking of the structural integrity of pressure vessels. Experimental data shows that the system can detect a surface crack as small as 4 mm and a through-crack as small as 2 mm in the high pressure engine pipe made of Inconel 718. It was found that the actuator-sensor paths that are most sensitive to crack growth are the ones in which the crack is growing away from, rather than towards the path. This discovery will provide important guidelines for the design of a sensor network for crack detection. It was also observed that the bending mode (equivalent to the A0 mode in plates) is more sensitive than the longitudinal mode (equivalent to the S0 mode in plates) to crack growth.

An Active Diagnostic System for Structural Health Monitoring of Rocket Engines

This paper presents a concept for active damage detection in a filament wound composite tube using a built-in diagnostic system. The proposed method uses piezoelectric transducers to generate and detect propagating stress waves. The diagnostic waves interact with structural defects and are scattered in all directions. These scattered waves carry information about the damage to the sensors. Extracting and interpreting this information is vital to the development of a robust structural health monitoring system. An experiment is described in which the location of damage is found by measuring the arrival times of the scattered waves. A method to estimate the size of the damage and the associated material degradation is also introduced.

Shawn J. Beard

Papers

Built-in sensor network for structural health monitoring of composite structure

Effect of adhesive on the performance of piezoelectric elements used to monitor structural health

An Active Diagnostic System for Structural Health Monitoring of Rocket Engines

Active damage detection in filament wound composite tubes using built-in sensors and actuators

Advances in the development of built-in diagnostic system for filament wound composite structures