Detection Of Induced Damage Research Articles

Detection of initiation of corrosion induced damage in concrete structures using nonlinear ultrasonic techniques.

Structural failure caused by corrosion of the reinforcing steel in concrete structures is quite common. In most cases, corrosion cracks appear on the surface at a late stage, leaving inadequate time for taking any measures. This paper investigates the detection of corrosion damage in reinforced concrete elements by using nonlinear ultrasonic (NLU) techniques. Various linear ultrasonic and NLU techniques were adopted to identify the most sensitive technique and ultrasonic parameters for corrosion induced damage detection at its early stage. It is observed that the linear techniques are not very effective in detecting corrosion induced damage. The sideband peak count-index (or SPC-I), a relatively new and promising technique, has been found to be an excellent indicator for the detection of corrosion induced damage initiation. However, its efficacy for detecting corrosion induced damage has not yet been reported. The present study shows that the SPC-I-based NLU technique outperforms (with the highest sensitivity) all other NLU techniques for detecting the onset of corrosion in steel and micro-crack formation in the surrounding material. As the corrosion progresses and cracks appear on the surface of the concrete, the efficiency of the SPC-I slowly weakens and other technique(s) are found to be quite efficient at that stage.

Corrosion induced damage detection of in-service RC slabs using acoustic emission technique

For early detection of structural deficiencies due to corrosion, real time damage detection systems are needed to be deployed. With regard to this, present paper explores efficacy of established acoustic emission (AE) based mathematical procedure for corrosion assessment of in-service RC slabs. Two RC slabs (undamaged and damaged due to corrosion) were monitored using AE, half-cell potential and concrete resistivity techniques. The results demonstrate that AE data, captured even for shorter duration, can indicate appropriate probability of corrosion. The corrosion probability predicted by AE technique is well validated with that of electrochemical techniques, establishing AE as a powerful technique for corrosion-induced damage detection of in-service structural elements.

Plasma process induced damage detection by fast wafer level reliability monitoring for automotive applications

Plasma process induced damage (PID) poses a device lifetime risk to all semiconductor products containing MOS gate dielectrics. This risk increases for smaller technology nodes. In this work we will present how to protect automotive products from PID. Products need to be made robust against PID by design checks with antenna rules determined in technology reliability qualifications. Additionally, damage that is invisible at zero hour, i.e. in parameter or product tests, needs to be detected by fast wafer level reliability (fWLR) monitoring on the fully produced wafer. The application and details of different stress types for charging cases are presented and discussed.

Heat Induced Damage Detection by Terahertz (THz) Radiation

Terahertz (THz) and sub-terahertz imaging and spectroscopy are becoming increasingly popular nondestructive evaluation techniques for damage detection and characterization of materials. THz radiation is being used for inspecting ceramic foam tiles used in TPS (Thermal Protection System), thick polymer composites and polymer tiles that are not good conductors of ultrasonic waves. Capability of THz electromagnetic waves in detecting heat induced damage in porous materials is investigated in this paper. Porous pumice stone blocks are subjected to long time heat exposures to produce heat induced damage in the block. The dielectric properties extracted from THz TDS (Time Domain Spectroscopy) measurements are compared for different levels of heat exposure. Experimental results show noticeable and consistent change in dielectric properties with increasing levels of heat exposure, well before its melting point.

Detection of Induced Damage in Medium-Density Fiberboard Panels Using a Neural Network Method

This research assessed the feasibility of using a neural network to detect induced and interior damage to small samples of medium-density fiberboard (MDF). The neural network was a 3-layer back-propagation network. The undamaged stress wave frequency spectrum patterns were used to train the neural network. In a previous study, we successfully used the trained patterns to evaluate low levels of damage in samples of MDF onto which various percentages of their estimated failure loads were applied. In this experiment, after introduction of grooves on the surface or a hole through the center of the samples, a small change in the wave patterns occurred. The neural network has the unique ability to train itself using data to recognize spectral patterns and was successfully used to detect structural damage.