Problems Associated with Statistical Pattern Recognition of Acoustic Emission Signals in a Compact Tension Fatigue Specimen

Acoustic emission (AE) data were acquired during fatigue testing of an aluminum 2024-T4 compact tension specimen using a commercially available AE system. AE signals from crack extension were identified and separated from noise spikes, signals that reflected from the specimen edges, and signals that saturated the instrumentation. A commercially available software package was used to train a statistical pattern recognition system to classify the signals. The software trained a network to recognize signals with a 91-percent accuracy when compared with the researcher's interpretation of the data. Reasons for the discrepancies are examined and it is postulated that additional preprocessing of the AE data to focus on the extensional wave mode and eliminate other effects before training the pattern recognition system will result in increased accuracy

Damage Diagnosis in Semiconductive Materials Using Electrical Impedance Measurements

Recent aerospace industry trends have resulted in an increased demand for real-time, effective techniques for in-flight structural health monitoring. A promising technique for damage diagnosis uses electrical impedance measurements of semiconductive materials. By applying a small electrical current into a material specimen and measuring the corresponding voltages at various locations on the specimen, changes in the electrical characteristics due to the presence of damage can be assessed. An artificial neural network uses these changes in electrical properties to provide an inverse solution that estimates the location and magnitude of the damage. The advantage of the electrical impedance method over other damage diagnosis techniques is that it uses the material as the sensor. Simple voltage measurements can be used instead of discrete sensors, resulting in a reduction in weight and system complexity. This research effort extends previous work by employing finite element method models to improve accuracy of complex models with anisotropic conductivities and by enhancing the computational efficiency of the inverse techniques. The paper demonstrates a proof of concept of a damage diagnosis approach using electrical impedance methods and a neural network as an effective tool for in-flight diagnosis of structural damage to aircraft components

Monitoring of chicken meat freshness by means of a colorimetric sensor array

A new optoelectronic nose to monitor chicken meat ageing has been developed. It is based on 16 pigments prepared by the incorporation of different dyes (pH indicators, Lewis acids, hydrogenbonding derivatives, selective probes and natural dyes) into inorganic materials (UVM-7, silica and alumina). The colour changes of the sensor array were characteristic of chicken ageing in a modi¿ed packaging atmosphere (30% CO2¿70% N2). The chromogenic array data were processed with qualitative (PCA) and quantitative (PLS) tools. The PCA statistical analysis showed a high degree of dispersion, with nine dimensions required to explain 95% of variance. Despite this high dimensionality, a tridimensional representation of the three principal components was able to differentiate ageing with 2-day intervals. Moreover, the PLS statistical analysis allows the creation of a model to correlate the chromogenic data with chicken meat ageing. The model offers a PLS prediction model for ageing with values of 0.9937, 0.0389 and 0.994 for the slope, the intercept and the regression coef¿cient, respectively, and is in agreement with the perfect ¿t between the predicted and measured values observed. The results suggest the feasibility of this system to help develop optoelectronic noses that monitor food freshness.Salinas Soler, Y.; Ros-Lis, JV.; Vivancos, J.; Martínez Mañez, R.; Marcos Martínez, MD.; Aucejo Romero, S.; Herranz, N.... (2012). Monitoring of chicken meat freshness by means of a colorimetric sensor array. Analyst. 137(16):3635-3643. doi:10.1039/C2AN35211GS3635364313716Anang, D. M., Rusul, G., Ling, F. H., & Bhat, R. (2010). Inhibitory effects of lactic acid and lauricidin on spoilage organisms of chicken breast during storage at chilled temperature. International Journal of Food Microbiology, 144(1), 152-159. doi:10.1016/j.ijfoodmicro.2010.09.014HINTON, A., & INGRAM, K. D. (2005). 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A colorimetric sensor array of porous pigments. The Analyst, 134(12), 2453. doi:10.1039/b916571aPalacios, M. A., Nishiyabu, R., Marquez, M., & Anzenbacher, P. (2007). Supramolecular Chemistry Approach to the Design of a High-Resolution Sensor Array for Multianion Detection in Water. Journal of the American Chemical Society, 129(24), 7538-7544. doi:10.1021/ja0704784Wu, Y., Na, N., Zhang, S., Wang, X., Liu, D., & Zhang, X. (2009). Discrimination and Identification of Flavors with Catalytic Nanomaterial-Based Optical Chemosensor Array. Analytical Chemistry, 81(3), 961-966. doi:10.1021/ac801733kJanzen, M. C., Ponder, J. B., Bailey, D. P., Ingison, C. K., & Suslick, K. S. (2006). Colorimetric Sensor Arrays for Volatile Organic Compounds. Analytical Chemistry, 78(11), 3591-3600. doi:10.1021/ac052111sSuslick, B. A., Feng, L., & Suslick, K. S. (2010). Discrimination of Complex Mixtures by a Colorimetric Sensor Array: Coffee Aromas. Analytical Chemistry, 82(5), 2067-2073. doi:10.1021/ac902823wHuang, X., Xin, J., & Zhao, J. (2011). A novel technique for rapid evaluation of fish freshness using colorimetric sensor array. Journal of Food Engineering, 105(4), 632-637. doi:10.1016/j.jfoodeng.2011.03.034Anzenbacher, Jr., P., Lubal, P., Buček, P., Palacios, M. A., & Kozelkova, M. E. (2010). A practical approach to optical cross-reactive sensor arrays. Chemical Society Reviews, 39(10), 3954. doi:10.1039/b926220mRos-Lis, J. V., García, B., Jiménez, D., Martínez-Máñez, R., Sancenón, F., Soto, J., … Valldecabres, M. C. (2004). Squaraines as Fluoro−Chromogenic Probes for Thiol-Containing Compounds and Their Application to the Detection of Biorelevant Thiols. Journal of the American Chemical Society, 126(13), 4064-4065. doi:10.1021/ja031987iRos-Lis, J. V., Martínez-Máñez, R., Rurack, K., Sancenón, F., Soto, J., & Spieles, M. (2004). Highly Selective Chromogenic Signaling of Hg2+in Aqueous Media at Nanomolar Levels Employing a Squaraine-Based Reporter. Inorganic Chemistry, 43(17), 5183-5185. doi:10.1021/ic049422qRos-Lis, J. V., Marcos, M. D., Mártinez-Máñez, R., Rurack, K., & Soto, J. (2005). A Regenerative Chemodosimeter Based on Metal-Induced Dye Formation for the Highly Selective and Sensitive Optical Determination of Hg2+ Ions. Angewandte Chemie International Edition, 44(28), 4405-4407. doi:10.1002/anie.200500583Ros-Lis, J. V., Martínez-Máñez, R., & Soto, J. (2005). Colorimetric Signaling of Large Aromatic Hydrocarbons via the Enhancement of Aggregation Processes. Organic Letters, 7(12), 2337-2339. doi:10.1021/ol050564dCliment, E., Marcos, M. D., Martínez-Máñez, R., Sancenón, F., Soto, J., Rurack, K., & Amorós, P. (2009). The Determination of Methylmercury in Real Samples Using Organically Capped Mesoporous Inorganic Materials Capable of Signal Amplification. 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