USING SPECTRAL ANALYSIS TO DETECT SENSOR NOISE AND CORRECT TURBULENCE INTENSITY AND SHEAR STRESS ESTIMATES FROM EMCM FLOW RECORDS
✍ Scribed by LAPOINTE, M. F.; SERRES, B. DE; BIRON, P.; ROY, A. G.
- Publisher
- John Wiley and Sons
- Year
- 1996
- Tongue
- English
- Weight
- 650 KB
- Volume
- 21
- Category
- Article
- ISSN
- 0360-1269
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✦ Synopsis
Electromagnetic current meters (EMCMs) are frequently used to gather turbulent velocity records in rivers and estuaries. Experience has shown that, on occasion, the output of these sensors can be affected by contamination from various noise sources. These noises may be limited to narrow bands of frequencies and thus fail to produce conspicuous increases in observed signal variance. Such 'narrow-band' noises can be difficult to identify from simple inspection of signal traces or variance levels, yet degrade estimates of turbulence statistics, in particular covariances (used to calculate Reynolds shear stress). This paper demonstrates the usefulness of spectral analysis to detect and characterize narrow-band noise components in turbulent flow records. Statistical principles underlying the use of spectral analysis for noise detection are briefly reviewed. Examples of u and v velocity spectra and cospectra are then presented from actual EMCM velocity records from flume and field deployments that were found to be contaminated by such noises. The sensitivity of the shear stress estimates to even minor noise levels is demonstrated. The use of spectral analysis to correct variance (turbulence intensity) and covariance (shear stress) estimates obtained from records contaminated by narrow-band noise is also illustrated.