scholarly journals Recurrent neural networks and proper orthogonal decomposition with interval data for real-time predictions of mechanised tunnelling processes

2018 ◽  
Vol 207 ◽  
pp. 258-273 ◽  
Author(s):  
S. Freitag ◽  
B.T. Cao ◽  
J. Ninić ◽  
G. Meschke
Keyword(s):  
Neural Networks ◽  
Proper Orthogonal Decomposition ◽  
Real Time ◽  
Recurrent Neural Networks ◽  
Interval Data ◽  
Orthogonal Decomposition ◽  
Proper Orthogonal ◽  
Mechanised Tunnelling

Experimental Application of a Damage Localisation Technique Based on Smoothed Proper Orthogonal Modes

2007 ◽  
Vol 347 ◽  
pp. 121-126 ◽  
Author(s):  
U. Galvanetto ◽  
L. Monopoli ◽  
Cecilia Surace ◽  
Alessandra Tassotti
Keyword(s):  
Damage Detection ◽  
Proper Orthogonal Decomposition ◽  
Real Time ◽  
Orthogonal Decomposition ◽  
Steel Beams ◽  
Acceleration Response ◽  
Experimental Application ◽  
Lab Experiments ◽  
Proper Orthogonal Modes ◽  
Proper Orthogonal

The paper presents an experimental application of the Proper Orthogonal Decomposition (POD) to damage detection in steel beams. A damaged beam has been excited with a sinusoidal force, the acceleration response at points regularly spaced along the structure has been recorded and the relevant Proper Orthogonal Modes calculated. In this way it is possible to locate damage by comparing the measured dominant Proper Orthogonal Mode with a smoothed version of it which does not exhibit apparent peaks in correspondence with the damage. One of the principal advantages of the proposed damage detection technique is that it does not require vibration measurements to be performed on the undamaged structure. Moreover the ‘optimality’ of the proper orthogonal modes only requires the use of a few (one-two) of them which can be computed in real time during lab experiments or while the structure is functioning in the field.

scholarly journals Rapid Reconstruction of Simulated and Experimental Temperature Fields Based on Proper Orthogonal Decomposition

2020 ◽  
Vol 10 (11) ◽  
pp. 3729
Author(s):  
Minxin Chen ◽  
Shi Liu ◽  
Shanxun Sun ◽  
Zhaoyu Liu ◽  
Yu Zhao
Keyword(s):  
Temperature Field ◽  
Numerical Methods ◽  
Proper Orthogonal Decomposition ◽  
Real Time ◽  
Orthogonal Decomposition ◽  
Reconstruction Method ◽  
Gas Combustion ◽  
Field Reconstruction ◽  
Proper Orthogonal ◽  
Temperature Field Reconstruction

Temperature information has a certain significance in thermal energy systems, especially in gas combustion systems. Generally, measurements and numerical calculations are used to acquire temperature information, but both of these approaches have their limitations. Constrained by cost and conditions, measurement methods are difficult to use to reconstruct the temperature field. Numerical methods are able to estimate the temperature field; however, the calculation process in numerical methods is very complex, so these methods cannot be used in real time. For the purpose of solving these problems, a two-dimensional temperature field reconstruction method based on the proper orthogonal decomposition (POD) algorithm is proposed in this study. In the proposed method, the temperature field reconstruction task is transformed into an optimization problem. Theoretical analysis and simulations show that the proposed method is feasible. Gas combustion experiments were also performed to validate this method. Results indicate that the proposed method can yield a reliable reconstruction solution and can be applied to real-time applications.

Kalman Filter Development for Real Time Proper Orthogonal Decomposition Disc Temperature Model

2016 ◽  
Author(s):  
Andrew van Paridon ◽  
Marko Bacic ◽  
Peter T. Ireland
Keyword(s):  
Kalman Filter ◽  
Proper Orthogonal Decomposition ◽  
Real Time ◽  
Best Practice ◽  
Simulated Data ◽  
Flight Simulation ◽  
Orthogonal Decomposition ◽  
Life Assessment ◽  
Thermal Dynamics ◽  
Proper Orthogonal

Extending disc life through online health monitoring has been a proven method of minimising engine downtime and maintenance costs. To properly monitor the disc requires a robust model of the disc’s non-linear thermal dynamics. A model can be improved by filtering the output using a measurement of the disc in real time. The damage models can then be computed with higher statistical confidence leading to increased safe life prediction. Recently, a model of disc temperature has been developed based on the proper orthogonal decomposition of simulated data. The model produced detailed thermal gradients for use in damage calculation and life assessment. This paper presents the development and implementation of a Kalman filter to augment that model. The location of the measurement has been assessed in order to select the most appropriate target for instrumentation. Points all around the front and back of the disc have been assessed, and the best practice result is found to be near the centre of the disc neck. Matching temperatures at this point represents a compromise between the fast dynamic response of the rim, with the slower response of the cob. The new model has been validated against an independent flight simulation that had previously been excluded from any training process. The addition of the Kalman filter allows the model to match aircraft dynamics outside the regular training trajectories. The accuracy is approximately ±30K, and there is a root-mean-square error of only 2K over the whole model at any one point in time.

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