Research on the detection effect of post-processing method of Acoustic Doppler Velocimetry data based on three-dimensional phase space thresholding method and robust estimation method

Zhong Chunyi; Zhang Junbo; Yang Zhenhao; Ji Shuheng; Wan Rong

doi:10.12284/hyxb2021132

Volume 43 Issue 8

Aug. 2021

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Article Navigation > Haiyang Xuebao > 2021 > 43(8): 152-159

Zhong Chunyi，Zhang Junbo，Yang Zhenhao, et al. Research on the detection effect of post-processing method of Acoustic Doppler Velocimetry data based on three-dimensional phase space thresholding method and robust estimation method[J]. Haiyang Xuebao，2021, 43(8)：152–159 doi: 10.12284/hyxb2021132

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Research on the detection effect of post-processing method of Acoustic Doppler Velocimetry data based on three-dimensional phase space thresholding method and robust estimation method

doi: 10.12284/hyxb2021132

Zhong Chunyi^1
,,
Zhang Junbo^{1, 2},
Yang Zhenhao¹,
Ji Shuheng¹,
Wan Rong^{1, 2, 3
,
,}

1.
School of Marine Science, Shanghai Ocean University, Shanghai 201306, China
2.
National Engineering Research Center for Oceanic Fisheries, Shanghai 201306, China
3.
Zhoushan Branch of National Engineering Research Center for Oceanic Fisherie, Zhoushan 316014, China

Received Date: 2021-01-05
Rev Recd Date: 2021-04-15

Available Online: 2021-05-19

Publish Date: 2021-08-25

Abstract

Abstract

Water flow is an important environmental factor that affects whether barnacles, oysters, algae, and other aquatic organisms can successfully attach to fishing equipment. Changes in water velocity will change the metabolism of algae and restrict the spread of barnacles and oyster larvae. The accuracy of the flow velocity data plays a vital role in studying the attachment mechanism of organisms attached to fishery equipment. Acoustic Doppler Velocimetry (ADV) is an important device for measuring the flow velocity. However, factors such as bubbles and large suspended solids in the water will affect the correlation coefficient and signal-to-noise ratio of ADV, resulting in outliers in the flow velocity data and reducing the accuracy of the data. Based on the domestic and foreign mainstream algorithms—robust estimation method and the three-dimensional phase space thresholding method, actual measured flow velocity data of ADV are taken as an example to compare and study the detection effects of the two post-processing methods. The results showed that the average detection rate of the robust estimation method was 4.95%, the kurtosis coefficient decreased by 77.71%, the average detection rate of the three-dimensional phase space thresholding method was 14.60%, and the kurtosis coefficient decreased by 84.05%. Comprehensive analysis showed that the three-dimensional phase space thresholding method had a better processing effect, and its detection accuracy was higher than that of the robust estimation method, but there was a phenomenon of overprocessing. It was recommended that the three-dimensional phase space thresholding method be used when dealing with data with an outlier content of less than 5%, and for data whose outliers deviate from the sample average, the robust estimation method was recommended. This article is of great significance for reducing the error of flow velocity data and accurately and quantitatively studying the influence of water flow on the attachment amount and types of fishery equipment attached organisms. It also provides a scientific basis for the subsequent development of a post-processing algorithm with high detection accuracy and less overprocessing.
- Acoustic Doppler Velocimetry,
- flow velocity data,
- data despiking,
- three-dimensional phase thresholding space,
- robust estimation

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References(23)

References

[1]	黄一心, 丁建乐, 鲍旭腾, 等. 中国渔业装备和工程科技发展综述[J]. 渔业现代化, 2019, 46(5): 1−8. doi: 10.3969/j.issn.1007-9580.2019.05.001 Huang Yixin, Ding Jianle, Bao Xuteng, et al. Development research on China fishery equipment and engineering technology[J]. Fishery Modernization, 2019, 46(5): 1−8. doi: 10.3969/j.issn.1007-9580.2019.05.001
[2]	杨宗澄, 白秀琴, 姜欢, 等. 船体表面海洋污损生物附着规律分析[J]. 船舶工程, 2016, 38(2): 29−33, 79. Yang Zongcheng, Bai Xiuqin, Jiang Huan, et al. Analysis of biofouling occurrence trends on ship hull surface[J]. Ship Engineering, 2016, 38(2): 29−33, 79.
[3]	王海涛, 张东兴, 郑岩. 防除海洋污损生物附着的技术研究进展[J]. 水产学杂志, 2018, 31(6): 47−50. doi: 10.3969/j.issn.1005-3832.2018.06.010 Wang Haitao, Zhang Dongxing, Zheng Yan. A review: research progress on prevention and removal technology of marine fouling organisms[J]. Chinese Journal of Fisheries, 2018, 31(6): 47−50. doi: 10.3969/j.issn.1005-3832.2018.06.010
[4]	Jadidi P, Zeinoddini M, Soltanpour M, et al. Towards an understanding of marine fouling effects on VIV of circular cylinders: aggregation effects[J]. Ocean Engineering, 2018, 147: 227−242. doi: 10.1016/j.oceaneng.2017.10.037
[5]	Balasubramanian V, Rajaram R, Palanichamy S, et al. Lanosterol expressed bio-fouling inhibition on Gulf of Mannar coast, India[J]. Progress in Organic Coatings, 2018, 115: 100−106. doi: 10.1016/j.porgcoat.2017.11.009
[6]	Crisp D J. The behaviour of barnacle cyprids in relation to water movement over a surface[J]. Journal of Experimental Biology, 1955, 32(3): 569−590. doi: 10.1242/jeb.32.3.569
[7]	廖平安, 胡秀琳. 流速对藻类生长影响的试验研究[J]. 北京水利, 2005(2): 12−14. Liao Ping’an, Hu Xiulin. Experimental study on the effect of flow velocity on algal growth[J]. Beijing Water Resources, 2005(2): 12−14.
[8]	严松, 吴浩, 孙大鹏, 等. 声学多普勒流速仪在水槽流速测量中的应用[J]. 实验室研究与探索, 2017, 36(5): 9−13. doi: 10.3969/j.issn.1006-7167.2017.05.003 Yan Song, Wu Hao, Sun Dapeng, et al. Application of acoustic Doppler velocimetry in flume flow experiment[J]. Research and Exploration in Laboratory, 2017, 36(5): 9−13. doi: 10.3969/j.issn.1006-7167.2017.05.003
[9]	Sharma A, Maddirala A K, Kumar B. Modiﬁed singular spectrum analysis for despiking acoustic Doppler velocimeter (ADV) data[J]. Measurement, 2018, 117: 339−346. doi: 10.1016/j.measurement.2017.12.025
[10]	Fugate D C, Friedrichs C T. Determining concentration and fall velocity of estuarine particle populations using ADV, OBS and LISST[J]. Continental Shelf Research, 2002, 22(11/13): 1867−1886.
[11]	Goring D G, Nikora V I. Despiking acoustic Doppler velocimeter data[J]. Journal of Hydraulic Engineering, 2002, 128(1): 117−126. doi: 10.1061/(ASCE)0733-9429(2002)128:1(117)
[12]	Cea L, Puertas J, Pena L. Velocity measurements on highly turbulent free surface flow using ADV[J]. Experiments in Fluids, 2007, 42(3): 333−348. doi: 10.1007/s00348-006-0237-3
[13]	Donoho D L, Johnstone I M. Ideal spatial adaptation by wavelet shrinkage[J]. Biometrika, 1994, 81(3): 425−455. doi: 10.1093/biomet/81.3.425
[14]	Rousseeuw P J. Robust estimation and identifying outliers[M]. 2nd ed. New York: McGraw-Hill, 1998.
[15]	Zhong Chunyi, Yin Fang, Zhang Junbo, et al. Optimized algorithm for processing outlier of water current data measured by acoustic Doppler velocimeter[J]. Journal of Marine Science and Engineering, 2020, 8(9): 655. doi: 10.3390/jmse8090655
[16]	Nikora V I, Goring D G. ADV measurements of turbulence: can we improve their interpretation[J]. Journal of Hydraulic Engineering, 1998, 124(6): 630−634. doi: 10.1061/(ASCE)0733-9429(1998)124:6(630)
[17]	Wahl T L. Discussion of “Despiking Acoustic Doppler Velocimeter Data” by Derek G. Goring and Vladimir I. Nikora[J]. Journal of Hydraulic Engineering, 2003, 129(6): 484−487. doi: 10.1061/(ASCE)0733-9429(2003)129:6(484)
[18]	Joanes D N, Gill C A. Comparing measures of sample skewness and kurtosis[J]. Journal of the Royal Statistical Society: Series D (The Statistician), 1998, 47(1): 183−189. doi: 10.1111/1467-9884.00122
[19]	Köse Ö. Various filtering algorithms used to eliminate outliers in velocity time series obtained by ADVs (acoustic Doppler velocimeter)[J]. Arabian Journal of Geosciences, 2013, 6(7): 2691−2697. doi: 10.1007/s12517-012-0523-8
[20]	Parsheh M, Sotiropoulos F, Porté-Agel F. Estimation of power spectra of acoustic-Doppler velocimetry data contaminated with intermittent spikes[J]. Journal of Hydraulic Engineering, 2010, 136(6): 368−378. doi: 10.1061/(ASCE)HY.1943-7900.0000202
[21]	Jesson M, Sterling M, Bridgeman J. Despiking velocity time-series—Optimisation through the combination of spike detection and replacement methods[J]. Flow Measurement and Instrumentation, 2013, 30: 45−51. doi: 10.1016/j.flowmeasinst.2013.01.007
[22]	Islam M R, Zhu D Z. Kernel density-based algorithm for despiking ADV data[J]. Journal of Hydraulic Engineering, 2013, 139(7): 785−793. doi: 10.1061/(ASCE)HY.1943-7900.0000734
[23]	Razaz M, Kawanisi K. Signal post-processing for acoustic velocimeters: detecting and replacing spikes[J]. Measurement Science and Technology, 2011, 22(12): 125404. doi: 10.1088/0957-0233/22/12/125404