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Showing 1 to 19 of 19 for “"Kohonen self-organizing map"”.
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Prediction of Fatigue Life in 7075-T6 Aluminum from Neural Network Analysis of Acoustic Emission Data
… emission (AE) data acquisition system, a Kohonen self-organizing map, and a back-propagation neural network, AE data from 7075-T6 aluminum specimens were used to classify failure mechanisms and predict the number of fatigue cycles to failure. AE waveforms were captured from 40 notched …
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Neural Network Fatigue Life Prediction in 7075-T6 Aluminum from Acoustic Emission Data
… An AE data acquisition system coupled with a Kohonen self organizing map and a back propagation neural network were used to perform the analysis. AE waveforms were recorded during fatigue cycling of twenty-four notched 7075-T6 aluminum specimens using broad-band piezoelectric transducers. A …
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Ultimate Compression After Impact Load Prediction in Graphite/Epoxy Coupons Using Neural Network and Multivariate Statistical Analyses
… of impact damaged graphite/epoxy coupons using a Kohonen self-organizing map (SOM) neural network and multivariate statistical regression analysis (MSRA). An optimized use of these data treatment tools allowed the generation of a simple, physically understandable equation that predicts the …
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Ultimate Strength Prediction in Fiberglass/Epoxy Beams Subjected to Three-Point Bending Using Acoustic Emission and Neural Networks
… a 13 processing element hidden layer for mapping, and a single processing element output layer for predicting the ultimate load. The network, trained on seven beams, was able to predict ultimate loads in the remaining eight beams with a worst case error of +4.34 percent, which was within …
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Classification of Acoustic Emission Signals from an Aluminum Pressure Vessel Using a Self-Organizing Map
… spectrum was calculated for each waveform. A Kohonen self-organizing map (SOM) was used to cluster the spectra. The network clustered the data on a two-dimensional feature space according to the source of the signal. A total of 3,600 power spectra were used to train the neural network, and …
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Low Proof Load Prediction of Ultimate Strengths of Fiberglass/Epoxy I-Beams Using Acoustic Emission
… ultimate load for further analysis.</p> <p>A Kohonen self-organizing map was utilized to separate each individual data point (hit) into failure mechanism clusters. Then a multiple linear regression analysis was performed using the percentage of hits associated with each failure mechanism along …
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Neural Network Detection of Fatigue Crack Growth in Riveted Joints Using Acoustic Emission
… onto a two-dimensional feature space using a Kohonen self organizing map (SOM). Then 132 crack growth and 137 rivet rubbing spectra were used to train a back-propagation neural network to provide automatic pattern classification. Although there was some overlap between the clusters mapped in …
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Neural Network Fatigue Life Prediction in Notched Aluminum Specimens from Acoustic Emission Data
… filtered and successfully classified using a Kohonen self-organizing map (SOM) to identify the plane stress and plane strain failure mode data. Furthermore, the early cycle (< 25% of fatigue life) AE amplitude distribution data from the test samples were used to predict fatigue lives using the …
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In-Flight Fatigue Crack Monitoring of an Aircraft Engine Cowling
… emission data acquisition system coupled with a Kohonen self organizing map neural network were used to perform the analysis.</p> <p>Fatigue cracking was responsible for ripping the top of a fuselage off an Aloha Airlines Boeing 737-200 as it carried passengers over the Pacific Ocean, killing …
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Acoustic Emission Fatigue Crack Monitoring of a Simulated Aircraft Fuselage Structure
… These signals were then classified using a Kohonen self organizing map (SOM) neural network. By using proper data filtering before the SOM was run and using the correct classification parameters, it was shown that this is a highly accurate method of classifying AE waveforms from fatigue …
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Detection of Fatigue Crack Growth in a Simulated Aircraft Fuselage
… This was accomplished here through the use of a Kohonen self-organizing map (SOM) neural network.</p> <p>In order to simulate a fuselage undergoing fatigue, a pressure vessel was constructed from a 0.040 inch thick 2024-T3 aluminum cylinder. The vessel contained a rivet line, a round hole with a …
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A graphical, self-organizing approach to classifying electronic meeting output.
… research in the application and evaluation of a Kohonen Self-Organizing Map (SOM) to the problem of classification of Electronic Brainstorming output. Electronic Brainstorming is one of the most productive tools in the Electronic Meeting System called GroupSystems. A major step in group problem …
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Early Damage State Criterion from a Fault-Seeded Helicopter Gear Using Acoustic Emission and Neural Networks
… frequency of the AE signals were input into the Kohonen Self-Organizing Map (KSOM) artificial neural network (ANN) function in NeuralWorks Professional II/Plus software to separate cracking signals from other mechanisms such as noise and plastic deformation. Visual inspection and statistical …
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Compression After Impact Load Prediction in Graphite/Epoxy Laminates Using Acoustic Emission and Artificial Neural Networks
… were conducted using ANNs. First, a Kohonen self-organizing map (SOM) neural network was constructed and optimized in order to separate the AE data into noise plus the various failure mechanisms thought to be experienced by composite laminates undergoing compression. It was hoped that …
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Damage Assessment and Strength Predictions in S-Glass/Epoxy Laminates Subjected to Low Energy Impact
… network (ANN) for classification. Specifically a Kohonen Self Organizing Map (SOM) was used to sort and classify the failure mechanisms that occurred within the weakened composites. The associated BVID failure modes, otherwise known as failure mechanisms, were believed to consist primarily of …
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Classification of In-Flight Fatigue Cracks in Aircraft Structures using Acoustic Emission and Neural Networks
… neural network. The neural network used was the Kohonen self-organizing map, as it is an excellent choice for the purpose of classification.</p> <p>Once the neural network was trained, it was possible to proceed to the second stage of the research. A support structure, identical to the one used …
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Acoustic Emission Signal Classification for Gearbox Failure Detection
… best. The clustering algorithms utilized are the Kohonen Self-organizing Map (SOM), k-mean and Gaussian Mixture Model (GMM). From the clustering iterations, the three cluster criterion algorithms were performed to observe the suggested optimal number of cluster by the criterions. The three …
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Non-intrusive two-phase flow regime identification and transport characterization in microchannels subject to uniform and non-uniform heat input
… determination of two-phase flow regimes using a Kohonen Self-Organizing Map. ^ To characterize the sensor impedance response, numerical simulations are implemented in two- and three-dimensions. Electrical simulations of the crosswise electrode geometry are performed to acquire both instantaneous …
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Combining Multivariate Statistical Methods and Spatial Analysis to Characterize Water Quality Conditions in the White River Basin, Indiana, U.S.A.
… multivariate method uses a combination of Kohonen Self-Organizing Maps, Cluster Analysis, and Support Vector Machines. The final models were tested with recent and independent data collected from stations in the Eagle Creek watershed, within the White River basin. In 6 out of 20 models the …