scholarly journals Measurement uncertainty analysis of field-programmable gate-array-based, real-time signal processing for ultrasound flow imaging

2020 ◽  
Vol 9 (2) ◽  
pp. 227-238 ◽  
Author(s):  
Richard Nauber ◽  
Lars Büttner ◽  
Jürgen Czarske
Keyword(s):  
Signal Processing ◽  
Computational Complexity ◽  
Measurement Uncertainty ◽  
Field Programmable Gate Array ◽  
Time Signal ◽  
Flow Imaging ◽  
Doppler Velocimetry ◽  
Spatiotemporal Resolution ◽  
Field Programmable ◽  
Gate Array

Abstract. Research in magnetohydrodynamics (MHD) aims to understand the complex interactions of electrically conductive fluids and magnetic fields. A promising approach for investigating complex instationary flow phenomena are lab-scale experiments with low-melting alloys. They require a noninvasive flow instrumentation for opaque liquids with a high spatiotemporal resolution, a low velocity uncertainty and a long measurement duration. Ultrasound Doppler velocimetry can achieve multiplane, multicomponential flow imaging with multiple linear ultrasound arrays. However the average raw data output amounts to 1.2 GBs−1 at a frame rate of 33 Hz in a typical configuration for 200 transducers. This usually prevents long-duration measurements when offline signal processing is used. In this paper, we propose an online signal-processing chain for pulsed-wave Doppler velocimetry that is tailored to the specific requirements of flow imaging for lab-scale experiments. The trade-off between measurement uncertainty and computational complexity is evaluated for different algorithmic variants in relation to the Cramér–Rao bound. By utilizing selected approximations and parameter choices, a prepossessing could be efficiently implemented on a field-programmable gate array (FPGA), enabling a typical reduction of the data bandwidth of 6.5:1 and online flow visualization. We validated the performance of the signal processing on a test rig, yielding a velocity standard deviation that is a factor of 3 above the theoretical limit despite a low computational complexity. Potential applications for this signal processing include multihour flow measurements during a crystal-growth process and closed-loop velocity feedback for model experiments.

Real-time signal processing in field programmable gate array based digital gamma-ray spectrometer

2020 ◽  
Vol 91 (10) ◽  
pp. 104707
Author(s):  
Yinyu Liu ◽  
Hao Xiong ◽  
Chunhui Dong ◽  
Chaoyang Zhao ◽  
Quanfeng Zhou ◽  
...  
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Field Programmable Gate Array ◽  
Gamma Ray ◽  
Time Signal ◽  
Gamma Ray Spectrometer ◽  
Field Programmable ◽  
Gate Array ◽  
Real Time Signal Processing

Application of FPGAs to High-Speed Condition Based Maintenance of Rolling Element Bearings

Volume 3 ◽  
2004 ◽  
Author(s):  
Mark Harriman ◽  
Farbod Zorriassatine ◽  
Rob Parkin ◽  
Mike Jackson ◽  
Jo Coy
Keyword(s):  
Signal Processing ◽  
Condition Monitoring ◽  
Execution Time ◽  
Field Programmable Gate Array ◽  
High Speed ◽  
Mechanical Engineering ◽  
Electronic Engineering ◽  
Bearing Condition Monitoring ◽  
Field Programmable ◽  
Gate Array

Field-Programmable Gate Array (FPGA) technology has been applied widely in electronic engineering and computing industries, but it has not had the same level of reception in other disciplines including mechanical engineering [1]. The purpose of this paper is to examine FPGA implementations of signal processing techniques that are used in the context of bearing condition monitoring. As the number of bearings can be large sparse sensor arrays are used to locate and detect their condition. The demands of realtime process monitoring [2] [3] can place a heavy burden upon the monitoring system. Field-Programmable Gate Array (FPGA) technology [4] in this application makes it possible to implement more sophisticated algorithms. These exploit its high-speed, parallel, reconfigurable architecture. Bring forth the advantages of FPGA technology to condition monitoring. The techniques covered are: cross-correlation, digital signal processing (DSP) Infinite Impulse Response (IIR) filters, neural networks and signature matching. The implemented designs are optimised for both execution time and the amount of logic area consumed. Results were obtained from each technique and were assessed and compared in terms of execution time and also the amount of logic consumed on the FPGA. Over the past 15 years FPGA technology has been applied extensively in electronic engineering but its scope has not been as vastly in mechanical engineering. The objective of this paper was to examine an application in mechanical engineering. Ideally this would be done with a mechanical engineering compatible approach, giving rise to a methodology, which would allow FPGA programming [5] to become a transferable skill.

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