Experimental investigation on validation of the mini wave gauge for ocean wave measurements in comparison to an acoustic doppler current profiler and HOBO

• Autorzy: Widiaratih Rikha , Putranto Ari Bawono , Maslukah Lilik , Wirasatriya Anindya , Satya Eridhani Dharma , Himawa Daenk

Identyfikatory

DOI

10.12912/27197050/195842

• Języki publikacji: EN

Abstrakty

EN

The real-time monitoring of ocean wave data is a crucial element in marine environmental monitoring and the development of marine resources. It is unfortunate that the majority of wave measurement devices remain challenging, relatively high-priced, and require sophisticated technology. This study investigates the validation of a new type of ocean wave measurement, designed based on the Mini Wave Gauge (MWG), using low-cost materials. The study utilizes an accelerometer sensor, specifically the ADXL335, which is converted to measure wave height, and the GY-271 designed to measure wave direction. This research addresses the validation of MWG by comparing measurements from the Acoustic Doppler Current Profiler (ADCP) and HOBO. The validation of wave height demonstrates high accuracy, with a MAPE percentage of 0.46% between MWG and ADCP, and 23.30% between MWG and HOBO. In contrast, the validation of MWG for wave direction by ADCP still requires improvement, with a MAPE of 36.75%. This is due to the sensor's sensitivity to the earth's magnetic field, which requires further improvement of the buoy design to accommodate the direction of incoming waves. Additionally, the MWG's sampling rate in milliseconds allows for analyzing wave characteristics based on wave periods using the Fast Fourier Transform (FFT) method.

Słowa kluczowe

EN

marine monitoring; wave measurement; low-cost material; accelerometer sensor; validation; Fourier transforms; wave characteristics

• Wydawca: Lubelski Oddział Polskiego Towarzystwo Inżynierii Ekologicznej ; Lublin University of Technology ; WNGB Wydawnictwo Naukowe
• Czasopismo: Ecological Engineering & Environmental Technology
• Rocznik: 2025
• Tom: Vol. 26, iss. 1
• Strony: 187--200
• Opis fizyczny: Bibliogr. 54 poz., rys.

Twórcy

autor

Widiaratih Rikha

• Department of Oceanography, Faculty of Fisheries and Marine Science, Universitas Diponegoro, Jl. Prof. Jacub Rois Tembalang, Semarang, 50275, Indonesia
• Department of Naval Architecture, Ocean & Marine Engineering, Faculty of Engineering, University of Strathclyde, 16 Richmond Street, Glasgow, G1 1XQ, United Kingdom

• https://orcid.org/0000-0001-6656-5790

autor

Putranto Ari Bawono

• Department of Industrial Technology, Vocational School Universitas Diponegoro, Jl. Prof. Jacub Rois Tembalang, Semarang, 50275, Indonesia

• https://orcid.org/0009-0002-0950-7513

autor

Maslukah Lilik

• Department of Oceanography, Faculty of Fisheries and Marine Science, Universitas Diponegoro, Jl. Prof. Jacub Rois Tembalang, Semarang, 50275, Indonesia

• https://orcid.org/0000-0003-3794-9212

autor

Wirasatriya Anindya

• Department of Oceanography, Faculty of Fisheries and Marine Science, Universitas Diponegoro, Jl. Prof. Jacub Rois Tembalang, Semarang, 50275, Indonesia

• https://orcid.org/0000-0003-1030-5126

autor

Satya Eridhani Dharma

• Director of Water and Air Police (Ditpolairud) Regional Police of Central Java, Jl. Yos Sudarso, No. 57, Semarang, Central Java 50174 Indonesia

• https://orcid.org/0009-0000-3369-9805

autor

Himawa Daenk

• Department of Oceanography, Faculty of Fisheries and Marine Science, Universitas Diponegoro, Jl. Prof. Jacub Rois Tembalang, Semarang, 50275, Indonesia

• https://orcid.org/0009-0006-8844-5195

Bibliografia

• 1. Adiningsih, S., Fadlilah, Y. N., Putranto, R. T., Agfanita, S., Bayrus, S., Iriani, R. N., Wicaksono, M., Ikhtiarino, S., Wulandari, S., Adyaksa, Y., Petrova, C. B., Ginanjar, S., Wirasatriya, A., Widiaratih, R., Sugianto, D. N., Kunarso, K., Susanto, R. D. (2022). An FFT-Based Method for Wave Decomposition from Wave and Tide Monitoring Using A01NYUB Sensor. Proceeding - 2022 IEEE Ocean Engineering Technology and Innovation Conference: Management and Conservation for Sustainable and Resilient Marine and Coastal Resources, OETIC, 30–37. https://doi.org/10.1109/ OETIC57156.2022.10176211
• 2. Barstow, S. F., Ueland, G., Krogstad, H. E., Fossum, B. A. (1991). The Wavescan second generation directional wave buoy. IEEE Journal of Oceanic Engineering, 16(3), 254–266. https://doi.org/10.1109/48.90882
• 3. Behrens, J., Olfe, C., Cameron, G., Bucciarelli, R., Timmerman, R., Wright, D., Lodise, J., Merrifield, S., Terrill, E. (2024). Coastal data information program: advances in measuring and modeling wave activity, climate, and extremes. Coastal Engineering Journal, 66(1), 3–16. https://doi.org/10.1080/2 1664250.2024.2308021
• 4. Bishop, C. T., & Donelan, M. A. (1987). Measuring waves with pressure transducers. Coastal Engineering, 11(4), 309–328. https://doi.org/10.1016/0378-3839(87)90031-7
• 5. Bouferrouk, A., Saulnier, J.-B., Smith, George. H., Johanning, L. (2016). Field measurements of surface waves using a 5-beam ADCP. Ocean Engineering, 112, 173–184. https://doi.org/10.1016/j.oceaneng.2015.12.025
• 6. Cavaleri, L. (1980). Wave measurement using pressure transducer. Oceanologica Acta, 3, 339–346. https://api.semanticscholar.org/ CorpusID:67825798
• 7. Chang, M. H., Lien, R. C., Yang, Y. J., Tang, T. Y. (2011). Nonlinear internal wave properties estimated with moored ADCP measurements. Journal of Atmospheric and Oceanic Technology, 28(6), 802– 815. https://doi.org/10.1175/2010JTECHO814.1
• 8. Chen, F. H., Shieh, H. L., Tu, J. F. (2023). Development of earthquake detection and warning system based on sensors. Sensors and Materials, 35(4), 1211–1220. https://doi.org/10.18494/SAM4116
• 9. Christensen, K. H., Röhrs, J., Ward, B., Fer, I., Broström, G., Saetra, Ø., Breivik, Ø. (2013). Surface wave measurements using a ship-mounted ultrasonic altimeter. Methods in Oceanography, 6, 1–15. https://doi.org/10.1016/j.mio.2013.07.002
• 10. Dally, W. R. (2018). Comparison of a mid-shelf wave hindcast to ADCP-measured directional spectra and their transformation to shallow water. Coastal Engineering, 131, 12–30. https://doi.org/10.1016/j.coastaleng.2017.10.009
• 11. De-gan, Z., Hao, X., Gao, G., Zhao, H. (2000). A method of FFT-based wavelet transform. Journal of Northeastern University, 21(6), 599–601.
• 12. Dhanak, M. R., & Xiros, N. I. (2016). Springer Handbook of Ocean Engineering. https://doi.org/10.1007/978-3-319-16649-0
• 13. Dwinovantyo, A., Manik, H. M., Prartono, T., Susilohadi, S. (2017). Quantification and analysis of suspended sediments concentration using mobile and static acoustic doppler current profiler instruments. Advances in Acoustics and Vibration. https://doi. org/10.1155/2017/4890421
• 14. Earle, M., & Bush, K. (1982). Strapped-down accelerometer effects on NDBO wave measurements. OCEANS 82, 838–848. https://doi.org/10.1109/ OCEANS.1982.1151908
• 15. Elwany, H., & Mahr, R. (2003). Deep water directional wave measurements from pressure, wave velocities and a three-axis accelerometer. Proceedings of the IEEE/OES Seventh Working Conference on Current Measurement Technology, 127–127. https://doi.org/10.1109/CCM.2003.1194298
• 16. Gilbert, R. L. G. (1970). The Bedford institute wave recorder. Journal of Geophysical Research, 75(27), 5215–5224. https://doi.org/10.1029/ JC075i027p05215
• 17. Grover, V., & Sharma, A. (2017). Prediction of earthquake using 3 axis accelerometer sensor (ADXL335) and ARDUINO UNO. International Journal of Science and Research (IJSR), 6(9), 1044–1047.
• 18. Hao-ran, S., Wenshuai, L., Yiming, Z. (2006). Using 3-Axis Accelerometer ADXL330 to High Accuracy Pedometer. Chinese Journal of Sensors and Actuators, 19(4).
• 19. Hassan, M. ul, & Bao, Q. (2020). A Field Calibration Method for Low-Cost MEMS Accelerometer Based on the Generalized Nonlinear Least Square Method. Multiscale Science and Engineering, 2(2–3), 135– 142. https://doi.org/10.1007/s42493-020-00045-2
• 20. Hodson, T. O. (2022). Root-mean-square error (RMSE) or mean absolute error (MAE): when to use them or not. Geoscientific Model Development, 15(14), 5481–5487. https://doi.org/10.5194/ gmd-15-5481-2022
• 21. Hoitink, A. J. F., Peters, H. C., Schroevers, M. (2007). Field verification of ADCP surface gravity wave elevation spectra. Journal of Atmospheric and Oceanic Technology, 24(5), 912–922. https:// doi.org/10.1175/JTECH2000.1
• 22. Huckfeldt, M., Wöske, F., Rievers, B., List, M. (2024). GRACE Follow-On accelerometer data recovery by high-precision environment modelling. Advances in Space Research, 73(12), 5783–5805. https://doi.org/10.1016/j.asr.2024.03.068
• 23. Liu, W. C., & Huang, W. C. (2021). Development of a three-axis accelerometer and large-scale particle image velocimetry (LSPIV) to enhance surface velocity measurements in rivers. Computers and Geosciences, 155. https://doi.org/10.1016/j. cageo.2021.104866
• 24. Lyman, T. P., Elsmore, K., Gaylord, B., Byrnes, J. E. K., Miller, L. P. (2020). Open wave height logger: An open source pressure sensor data logger for wave measurement. Limnology and Oceanography: Methods, 18(7), 335–345. https://doi.org/10.1002/ lom3.10370
• 25. Lyzenga, D. R. (2015). Real-time estimation of ocean wave fields from marine radar data. IGARSS : 2015 IEEE International Geoscience & Remote Sensing Symposium : Proceedings : July 26–31, Milan, Italy, 3622–3625.
• 26. Ma, Z., Choi, J., Lee, J., Sohn, H. (2025). Accelerometer-aided millimeter-wave radar interferometry for uninterrupted bridge displacement estimation considering intermittent radar target occlusion. Mechanical Systems and Signal Processing, 223. https://doi.org/10.1016/j.ymssp.2024.111888
• 27. Mangkusasmito, F., Tadeus, D. Y., Winarno, H., Winarno, E. (2020). Accuracy improvement of gy-521 mpu-6050 sensor with drift factor correction method. Ultima Computing : Jurnal Sistem Komputer, 12(2), 91–95. https://doi.org/10.31937/ sk.v12i2.1791 (In Bahasa).
• 28. Bachtiar, M. M., Wibowo, I. K., Rifa’I, Y., Subagja, D. P., Syahriyah, N. A. (2023). Estimation of axis roll pitch of GY-91 IMU sensor reading using kalman filter. International Journal of Artificial Intelligence & Robotics (IJAIR), 5(2), 63–70. https://doi.org/10.25139/ijair.v5i2.7179
• 29. Ismail, M. I. M., Dziyauddin, R. A., Salleh, N. A. M., Ahmad, R., Azmi, M. H.B., Kaidi, H. M. (2018). Analysis and procedures for water pipeline leakage using three-axis accelerometer sensors: ADXL335 and MMA7361. IEEE Access, 6, 71249–71261. https://doi.org/10.1109/ACCESS.2018.2878862
• 30. Mon, Y.-J. (2015). The gyroscope sensor test by using Arduino platform. International Journal of Scientific & Technology Research, 4, 398–400.
• 31. Qi, F., Chen, G., Zhao, X., Wang, X. (2024). A high-precision positioning method for shield tunneling based on dual-axis hybrid inertial navigation system. Measurement: Journal of the International Measurement Confederation, 224. https://doi.org/10.1016/j.measurement.2023.113915
• 32. Quefeulou, P. 2004. Long-term validation of wave height measurements from altimeters. Marine Geodesy, 27(3–4), 495–510. https://doi.org/10.1080/01490410490883478
• 33. Rao, K., & Shubhanga, K. N. 2018. MAPE - an alternative fitness metric for prony analysis of power system signals. International Journal of Emerging Electric Power Systems, 19(6). https://doi. org/10.1515/ijeeps-2018-0091
• 34. Risandi, J., Solihuddin, T., Kepel, T. L., Daulat, A., Heriati, A., Mustikasari, E., Hidayat, R. (2022). Low-cost investigation of wave dynamics across low energy reef environments in Indonesia. IOP Conference Series: Earth and Environmental Science, 1119(1). https://doi.org/10.1088/1755-1315/1119/1/012033
• 35. Sharma, R., Kumar, P., Ojha, S., Gargari, S., Chopra, S. (2020). Inter-university accelerator centre, New Delhi (IUACD) radiocarbon date list I. Radiocarbon, 62(5), e1–e13. https://doi.org/10.1017/ RDC.2020.44
• 36. Shih, H. H., Long, C., Bushnell, M., Hathaway, K. (2005). Intercomparison of Wave Data Between Triaxys Directional Wave Buoy, ADCP, and Other Reference Wave Instruments. 24th International Conference on Offshore Mechanics and Arctic Engineering, 2, 655–663. https://doi.org/10.1115/ OMAE2005-67235
• 37. Shiina, T. (2019). Sea wave dynamics visualization and its interaction with the surface atmosphere by LED mini-lidar. In C. R. Bostater, X. Neyt, & F. Viallefont-Robinet (Eds.), Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions, 11150, 21. SPIE. https://doi.org/10.1117/12.2533406
• 38. Shimura, T., Mori, N., Baba, Y., Miyashita, T. (2022). Ocean surface wind estimation from waves based on small GPS buoy observations in a bay and the open ocean. Journal of Geophysical Research: Oceans, 127(9). https://doi.org/10.1029/2022JC018786
• 39. Shonting, D., Middleton, F., Knox, J., Hebda, P. (1996). A submarine-launched wave measuring buoy. Ocean Engineering, 23(6), 465–481. https://doi.org/10.1016/0029-8018(95)00055-0
• 40. Sorensen, R. M. (1993). Basic wave mechanics: for coastal and ocean engineers. A Wiley-Interscience Publication, John Wiley & Sons. 304.
• 41. Steele, K. E. (2003). Pitch-roll buoy mean wave directions from heave acceleration, bow magnetism, and starboard magnetism. Ocean Engineering, 30(17), 2179–2199. https://doi.org/10.1016/ S0029-8018(03)00082-9
• 42. Sugizaki, G., Takenaka, T., Toda, K. (1993). Motion characteristics measurement of rotating object using surface acoustic wave oscillator. Japanese Journal of Applied Physics, 32, 4237. https://doi. org/10.1143/JJAP.32.4237
• 43. Sui, L., Wang, J., Yang, X., Wang, Z. (2020). Spatial-temporal characteristics of coastline changes in Indonesia from 1990 to 2018. Sustainability, 12(8). https://doi.org/10.3390/su12083242
• 44. Tandon, A., Venkatesan, R., D’Asaro, E., Atmanand, M. (2018). Observing the Oceans in Real Time,. (Eds.), https://doi.org/10.1007/978- 3-319-66493-4, 323 Springer pub., http://www. springer.com/us/book/9783319664927. https://doi. org/10.1007/978-3-319-66493-4
• 45. Toffoli, A., & Bitner‐Gregersen, E. M. (2017). Types of ocean surface waves, wave classification. In Encyclopedia of Maritime and Offshore Engineering, 1–8. Wiley. https://doi.org/10.1002/9781118476406.emoe077
• 46. Trenaman, N., Devine, P., Strong, B. (2002). ADCP-based multidirectional wave gauge and current profiling. Oceans ’02 MTS/IEEE, 1763–1766. https:// doi.org/10.1109/OCEANS.2002.1191900
• 47. Valada, A., Velagapudi, P., Kannan, B., Tomaszewski, C., Kantor, G., Scerri, P. (2014). Development of a low cost multi-robot autonomous marine surface platform. Springer Tracts in Advanced Robotics, 92, 643–658. https://doi. org/10.1007/978-3-642-40686-7_43
• 48. Vashisth, R., Sharma, A., Malhotra, S., Deswal, S., Budhraja, A. (2017). Gesture Control Robot Using Accelerometer. ISPCC 2017 : 4th IEEE International Conference on Signal Processing, Computing and Control : September 21–23, 150–153.
• 49. Wei, Y., Lu, Z., Zhang, J.-K. (2016). A novel method to retrieve sea wave components from radar image sequence. 2016 IEEE International Conference on Mechatronics and Automation, 1691–1696. https://doi.org/10.1109/ICMA.2016.7558818
• 50. Widiaratih, R., Suryoputra, A. A. D., Handoyo, G., Satriadi, A., Putranto, A. B. (2023). Prototype of simple mini-wave gauge using Microcontroller ESP32 on the laboratory scale. IOP Conference Series: Earth and Environmental Science, 1224(1). https://doi.org/10.1088/1755-1315/1224/1/012024
• 51. Yevnin, Y., & Toledo, Y. (2022). A Deep Learning Model for Improved Wind and Consequent Wave Forecasts. https://doi.org/10.1175/JPO-D-21
• 52. Yu, Y., Gu, L., Wu, X. (2013). The Application of Artificial Intelligence in Ocean Development. Advanced Materials Research, 864–867, 2116– 2119. https://doi.org/10.4028/www.scientific.net/ AMR.864-867.2116
• 53. Zhang, A., Wang, W., Bi, W., Huang, Z. (2024). A path planning method based on deep reinforcement learning for AUV in complex marine environment. Ocean Engineering, 313, 119354. https://doi.org/10.1016/j.oceaneng.2024.119354
• 54. Zhao, N. (2010). Full-featured pedometer design realized with 3-Axis digital accelerometer. Analog Dialogue, 44(6).