Health Monitoring Of Composite Structures Based On Acoustic Wave Sensing Using Fiber Optic Sensors

Structural Health Monitoring has gained wide acceptance in the recent past as a means to monitor a structure and provide an early warning of an unsafe condition using real-time data. Utilization of structurally integrated, distributed sensors to monitor the health of a structure through accurate interpretation of sensor signals and real-time data processing can greatly reduce the inspection burden. The rapid improvement of the Fiber Optic Sensor technology for strain, vibration, ultrasonic and acoustic emission measurements in recent times makes it feasible alternative to the traditional strain gauges, PVDF and conventional Piezoelectric sensors used for Non Destructive Evaluation (NDE) and Structural Health Monitoring (SHM). Optical fiber-based sensors offer advantages over conventional strain gauges, and PZT devices in terms of size, ease of embedment, immunity from electromagnetic interference (EMI) and potential for multiplexing a number of sensors. The objective of this paper is to demonstrate the acoustic wave sensing using Extrinsic Fabry-Perot Interferometric (EFPI) sensor on a GFRP composite laminates. For this purpose experiments have been carried out initially for strain measurement with Fiber Optic Sensors on GFRP laminates with intentionally introduced holes of different sizes as defects. The results obtained from these experiments are presented in this paper. Numerical modeling has been carried out to obtain the relationship between the defect size and strain.

Discrimination of Nuclear Grade Steel Samples Subjected to Different Heat Treatment Procedures Based on Acoustic Emission (AE) Data Profiling at Crack Initiation

The present work is an attempt to study crack initiation in nuclear grade, 9Cr-1Mo ferritic steel using AE as an online NDE tool. Laboratory experiments were conducted on 5 heat treated Compact Tension (CT) specimens made out of nuclear grade 9Cr-1Mo ferritic steel by subjecting them to cyclic tensile load. The CT Specimens were of 12.5 mm thickness. The Acoustic emission test system was setup to acquire the data continuously during the test by mounting AE sensor on one of the surfaces of the specimen. This was done to characterize AE data pertaining to crack initiation and then discriminate the samples in terms of their heat treatment processes based on AE data. The AE signatures at crack initiation could conclusively bring to fore the heat treatment distinction on a sample to sample basis in a qualitative sense.Thus, the results obtained through these investigations establish a step forward in utilizing AE technique as an on-line measurement tool for accurate detection and understanding of crack initiation and its profile in 9Cr-1Mo nuclear grade steel subjected to different processes of heat treatment.