Implementation of Frequency-Based Classification of Damages in Composites Using Real-Time FPGA-Based Hardware Framework

Author(s):  
Adauto P. A. Cunha ◽  
Sebastian F. Wirtz ◽  
Dirk Söffker ◽  
Nejra Beganovic

Structural Health Monitoring (SHM) systems become an integral part of most technical systems in recent years. An integration of SHM in technical systems is closely related to: i) providing the guaranteed service lifetime of a system, ii) scheduled/planned maintenance actions, and iii) optimized system operation. For these purposes, different system variables can be monitored and utilized for an estimation of aging level of the system. Monitored system variables are therefore correlated to stochastically occurring damage, indirectly also to Remaining Useful Lifetime (RUL). Among challenges related to SHM, high attention is given to the reduction of a large amount of measured data and its real-time signal processing. In this contribution, classification of damages in composite materials using measurements of Acoustic Emission (AE) is proposed. Here, Discrete Wavelet Transform (DWT) is applied to AE signal to identify different damages in composites. As AE-signal is found in high frequency bandwidth, the amount of data captured in a short time period is enormous. Consequently, the calculation of DWT of such signal requires processing time quite far from real time and delays the entire classification procedure. Due to this, real-time implementation of DWT is proposed to cope with huge amount of captured data in this case and to reduce the time required for signal processing. Using FPGA-based system, real-time implementation of DWT is shown. Obtained results are compared with the results of offline DWT calculation to prove the efficiency and accuracy of real-time implementation.

2020 ◽  
Vol 91 (10) ◽  
pp. 104707
Author(s):  
Yinyu Liu ◽  
Hao Xiong ◽  
Chunhui Dong ◽  
Chaoyang Zhao ◽  
Quanfeng Zhou ◽  
...  

2013 ◽  
Vol 333-335 ◽  
pp. 650-655
Author(s):  
Peng Hui Niu ◽  
Yin Lei Qin ◽  
Shun Ping Qu ◽  
Yang Lou

A new signal processing method for phase difference estimation was proposed based on time-varying signal model, whose frequency, amplitude and phase are time-varying. And then be applied Coriolis mass flowmeter signal. First, a bandpass filtering FIR filter was applied to filter the sensor output signal in order to improve SNR. Then, the signal frequency could be calculated based on short-time frequency estimation. Finally, by short window intercepting, the DTFT algorithm with negative frequency contribution was introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and the phase difference obtained, the time interval of two signals was calculated. Simulation results show that the algorithms studied are efficient. Furthermore, the computation of algorithms studied is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.


2011 ◽  
Vol 14 (1) ◽  
pp. 1-14 ◽  
Author(s):  
T. Le Sage ◽  
A. Bindel ◽  
P. P. Conway ◽  
L. M. Justham ◽  
S. E. Slawson ◽  
...  

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