Katsuhiko Osaka

Strain monitoring of braided composites by using embedded fiber-optic strain sensors

Recently, fiber optic strain sensors have been applied to internal strain and damage monitoring of composites because of their small size, light weight and flexibility. Braided fiber reinforced plastics (FRP) are compatible with fiber optic sensors because optical fibers can be integrated directly and easily into fabrics. In the present paper, the strain monitoring of braided glass fiber reinforced plastics (GFRP) was conducted by using embedded fiber Bragg grating (FBG) and extrinsic Fabry–Perot interferometric (EFPI) sensors during the cure process, tensile tests and fatigue tests. From the experimental results of cure monitoring, it was found that both sensors can be used only for monitoring of thermal residual strain during cooling process. From the results of tensile tests, it was found that both sensors could measure strain correctly until damage initiation of braided GFRP. It also appeared that FBG sensors could monitor damage to FRP by observing the reflected spectral shape. From the fatigue tests, it appeared that the strain measured by embedded FBG sensors was affected by fatigue damage. Therefore, it is concluded that internal strain monitoring of braided FRP using fiber optic strain sensors is very useful for cure and health monitoring.

Smart autoclave processing of thermoset resin matrix composites based on temperature and internal strain monitoring

Cure cycle optimization and process control for autoclave cure of thermoset resin matrix composites based on temperature and internal strain monitoring were studied. Cure of thermoset resin is usually an exothermic reaction, which causes temperature increase of composites during cure. Slowing down the temperature ramp rate is effective in lowering the peak temperature. However, the slower is the ramp rate, the longer the cure time becomes. Therefore, it is desirable to control the ramp rate in order to depress the peak temperature with prolongation of cure time minimized. Besides that, precise determination of cure completion is also required in order to minimize cure time. The procedure for smart processing described above was developed and tried on laminate of carbon fiber/epoxy resin prepreg. In this procedure, temperature ramp rate is controlled so that the peak temperature predicted by Springers thermochemical model is kept below an allowable value. Cure completion is determined by a cure rate equation and internal strain monitoring with embedded EFPI optical fiber sensors. The internal strain is correlated with specific volume change of the matrix resin caused by cure shrinkage and thermal expansion/contraction. The authors found that the cure shrinkage terminates at a certain degree of cure, and EFPI sensors can detect this point. Although the degree of cure can be calculated by integrating the cure rate equation along temperature history, errors may be accumulated. Therefore, the degree of cure is corrected and integration of cure rate equation is restarted at the cure shrinkage termination point detected by EFPI sensors. Thus, cure completion is determined precisely. This smart autoclave processing procedure was able to depress the peak temperature and determine the end of cure.

Report on a simultaneous ion viscosity, strain and impedance measurement technique using a novel integrated dielectric, optical fiber and piezoelectric sensing element for the online characterization of smart structures

This paper reports on a simultaneous ion viscosity, strain and impedance (SISI) system in order to measure the physical and chemical properties of composites during their curing process. The SISI system uses an integrated multi-sensing element, entitled DOP, that is comprised of dielectric (D), optical fiber (O) and piezoelectric (P) sensors. This system was used to measure several data simultaneously in real time and in situ. The results clearly show that there is a direct relationship between the ion viscosity, impedance and strain changes during the curing process. It was found that dielectric sensor is very sensitive to physical and chemical changes of the composite both in the heating and cross-linking periods. The piezoelectric proved to be a useful element during the heating period with a very sensitive and surprising behavior during the cooling period. The optical fiber also demonstrated a very striking profile in strain variations during cooling.

Fiber optic strain monitoring of textile GFRP during RTM molding and fatigue tests by using embedded FBG sensors

This paper describes cure and health monitoring of glass fiber reinforced plastics (GFRP) textile composites both during a resin transfer molding (RTM) process and in loading tests. Carbon fiber reinforced plastics (CFRP) textile composites also were used for a comparative study. Fiber Bragg grating (FBG) fiber optic sensors were embedded in FRP to monitor internal strain. From the results of cure monitoring, it was found that the embedded FBG sensors were useful to know when cured resin constrained fibers. It also appeared that specimens were subjected to friction stress resulted from difference of coefficient of thermal expansion between FRP and a stainless steel mold in cooling process of RTM molding. After the molding, tensile and fatigue tests were conducted. The results of tensile tests showed that output of the embedded FBG sensors agreed well that of surface-bonded strain gauges despite deterioration of reflected spectra form the sensors. From the results of fatigue tests, the FBG sensors showed good status until 100,000 cycles when specimens had no damage. From these results, it can be concluded that embedded FBG sensors have good capability of monitoring internal strain in textile FRP both during RTM process and in service.

Pattern recognition application in classification of intelligent composites during smart manufacturing using a C4.5 machine learning program

The development of an on line computer based classification system for the real time classification of different composites is addressed in this study. Different parameters were collected simultaneously when embeded sensors (dielectric, optical fiber, and piezoelectric sensors) were used within two different composite matrices during the curing process. The measurements were used by an algorithm software as a logged data file, resulting in to inducing a decision tree. Later, a systematic software is designed based on the rules derived from this decision tree, to recognise the type of composites used in the experiment together with recognition of their physical and mechanical characteristics. This is a new approach to data acquisition in intelligent materials produced by smart manufacturing system.

Damage Behavior of Adhesive Butt Joints Bonded with Rubber-Modified Epoxy.

In the present study, damage behavior in the adhesive layer of adhesive butt joints bonded with rubber-modified epoxy was investigated by using an anisotropic damage theory. In the experiments, the stress-strain curves of the bulk specimens and the adhesive layer in the butt joints were measured by loading-unloading tests at a relatively low strain rate. The values of damage parameter D1 in the maximum principal stress direction were obtained from the measured stress-strain curves for the specimens. The relation between D1 and the strain energy density given to the specimens was investigated in order to compare the damage behavior of the butt joint and bulk specimens. From the results, it was found that the strain energy density of the specimens given until they break increased with rubber contents, but their damage behaviors were almost the same. It was also found that the strain energy densities of the specimens at their fracture were almost the same but the damage parameter D1 of the butt joint specimen was higher than that of the bulk specimen over the full range of strain energy.

Failure behaviors of cylindrical adhesively bonded joints of FRP under combined bending and torsional loadings.

In this paper the strength and the process to failure of the cylindrical adhesively bonded joints of fiber reinforced plastics have been investigated under combined bending and torsional loading conditions. Experiments were performed with an apparatus capable of applying bending and torsional moments in various proportions. From the results of the strength under combined bending and torsional loading, it was found that the failure criterion of cylindrical joints of FRP was expressed by an elliptic form equation. In order to know the extent of damage in the joint, strains and AE in this part were measured in tensile, bending, torsional and combined bending and torsional loading tests. From these results it became clear that the failure of cylindrical adhesive joints was mainly in the adhesive layer under tensile loading, while under other loading conditions damage was undergone in adherent. It was also found that the damage region in the joint was characterized by the loading conditions. It was observed that under the bending condition the central area of the joint was mainly damaged and with increase of the ratio of the torsional moment to the bending moment, the main damage area was extended to the joint end.

Simulation of low cycle fatigue failure of glass-mat FRP by AE method.

Previously it has been shown that AE ring-down counts of glass-mat FRP in low-cycle fatigue loading become steady at the comparatively initial stage and their amounts are approximately linear with the fatigue life on a log-log diagram. In the present study, it was found that AE ring-down counts at each cycle during low-cycle fatigue could be evaluated from the strain response at the corresponding cycle by using the relation between strain and AE counts in static tests. It was also shown that the strain at each cycle during fatigue could be represented by the secant modulus and the modulus under unloading, and that both moduli at each cycle could be calculated from the applied stress and the secant modulus at the first cycle of the fatigue tests. Based on these concepts and then using the above-mentioned relation between AE counts and fatigue life, the prediction of low-cycle fatigue failure was made by a simulation method. A rather good agreement between the simulated and tested results was obtained.