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Su boru hatlarında sızıntı konum tespiti için genişletilmiş kalman filtresi tabanlı IMU sensör füzyonu uygulaması

Year 2017, Volume: 32 Issue: 4, 1393 - 1404, 08.12.2017
https://doi.org/10.17341/gazimmfd.369872

Abstract

Su
dağıtım şebekelerinde, borulardaki çatlaklar ve arızalardan dolayı ciddi
miktarda su kaybı yaşanmaktadır. Bu arızaların kısa zamanda tespit edilerek
onarılması, su ve buna bağlı oluşan gelir kaybının önlenmesi için oldukça
önemlidir. Dağıtım şebekelerinde yüksek maliyete sahip genel onarım işlemleri
yerine, arızanın kesin konumunun bulunup sadece o bölgede çalışma yapılması
onarım maliyetlerini azaltacaktır. Her ne kadar yüzeysel boru dinleme cihazları
bu ihtiyaca bir çözüm olarak görünse de, dış ortam seslerinden etkilenmesi bu
yöntemin verimliliğini düşürdüğünden tercih edilmemesine neden olmaktadır.
Ticari olarak piyasada mevcut olan modern GPS temelli sistemler, büyük çaplı su
borularında çalışabilir (≥6 inch) ve yüksek maliyetlere sahiptir. Bu çalışmada
daha küçük çaplı borularda ve GPS sistemine ihtiyaç duymadan çalışabilecek bir
sızıntı tespit robotu prototipinin ön çalışması sunulmuştur. Bu ön çalışmada,
boru içerisinde suyun itme kuvvetiyle hareket edecek robotun tasarımı, üretimi,
konum ve sızıntı tahmin yazılımları gerçekleştirilmiştir. Konum tahmini, 9-dof
IMU sensör (3D-ivme, 3D-jiroskop ve 3d-manyetometre) verilerinin Genişletilmiş
Kalman Filtresi içerisinde kullanımıyla yapılmaktadır. Sızıntı tahmini, anlık
kaydedilen ses verisindeki tepe noktalara karşılık gelen konumun tespitini
içermektedir. Yapılan deneysel çalışmalarda, toplam 118m gezintide sonucunda
sızıntı konumu tahmin hatasının yaklaşık 0,25m olduğu görülmüştür.

References

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  • 2. Ulaş A., Ovalı P.K., A New Approach to Concentric Circles Theory As Urban Growth Model in Concept of Physical Theories: Force Model within Kinetic and Potential Urbanization, Journal of the Faculty of Engineering and Architecture of Gazi University, 32 (2), 393-401, 2017.
  • 3. Mcneill L.S., Edwards M., Iron Pipe Corrosion in Distribution Systems, J. Am. Water Works Assn., 93 (7), 88-100, 2001.
  • 4. Alegre H., Baptista J.M., Jr E.C., Performance Indicators for Water Supply Services: Third Edition, IWA Publishing, London, United Kingdom, 2016.
  • 5. Marin P., Kingdom B., Liemberger R., The Challenge of Reducing Non-Revenue Water (Nrw) in Developing Countries - How The Private Sector Can Help : A Look at Performance-Based Service Contracting, The World Bank, 39405, December 2006.
  • 6. Hooda S.M., Rajasthan Water Assessment : Potential for Private Sector Interventions, International Finance Corporation, World Bank, New Delhi, 2017.
  • 7. Puust R., Kapelan Z., Savic D.A., Koppel T., A Review of Methods For Leakage Management in Pipe Networks, Urban Water J., 7 (1), 25-45, 2010.
  • 8. Hunaidi O., Wang A., Bracken M., Gambino T., Fricke C., Acoustic Methods for Locating Leaks in Municipal Water Pipe Networks, International Conference on Water Demand Management, Dead Sea-Jordan, 1-14, May 30- June 3, 2004.
  • 9. Sewerin AQUAPHON 200 Leak-Survey-Tool. http://muinin.com/aquaphon-a-200/. Erişim tarihi: Ocak 4, 2017.
  • 10. Lay-Ekuakille A., Griffo G., Vergallo P., Robust Algorithm Based on Decimated Padè Approximant Technique for Processing Sensor Data in Leak Detection in Waterworks, IET Sci. Meas. Technol., 7 (5), 256-264, 2013.
  • 11. Ben-Mansour R., Habib M.A., Khalifa A., Youcef-Toumi K., Chatzigeorgiou D., Computational Fluid Dynamic Simulation of Small Leaks in Water Pipelines for Direct Leak Pressure Transduction, Comput. Fluids, 57, 110-123, 2012.
  • 12. Begovich O., Pizano-Moreno A., Garcia-Malacara E., Besançon G., How Can The Temperature Affect the Performance of a Classical Pipeline Model When Plastic Pipes Are Used?, 8th International Conference on Electrical Engineering, Computing Science and Automatic Control, Merida City-Mexico, 1-6, October 26-28, 2011.
  • 13. Goh J.H., Water Pipe Leak Detection Using Electromagnetic Wave Sensor for the Water Industry, 2011 IEEE Symposium on Computers Informatics, Kuala Lumpur-Malaysia, 290-295, March 20-23, 2011.
  • 14. Lay-Ekuakille A., Vendramin G., Trotta A., Robust Spectral Leak Detection of Complex pipelines Using Filter Diagonalization Method, IEEE Sens. J., 9 (11), 1605-1614, 2009.
  • 15. Daneti M., On Using Double Power Spectral Density Information for Leak Detection, 2013 IEEE International Conference on Industrial Technology, Cape Town-Western Cape-South Africa, 1162-1167, February 25-28, 2013.
  • 16. Kadri A., Abu-Dayya A., Stefanelli R., Trinchero D., Characterization of an Acoustic Wireless Sensor for Water Leakage Detection in Underground Pipes, 2013 1st International Conference on Communications, Signal Processing and Their Applications, Sharjah-United Arab Emirates, 1-5, February 12-14 ,2013.
  • 17. Ridao P., Carreras M., Ribas D., Garcia R., Visual Inspection of Hydroelectric Dams Using an Autonomous Underwater Vehicle, J. Field Rob., 27 (6), 759-778, 2010.
  • 18. Cataldo A., Cannazza G., Benedetto E. D., Giaquinto N., A New Method for Detecting Leaks in Underground Water Pipelines, IEEE Sens. J., 12 (6), 1660-1667, 2012.
  • 19. Zhang L., Wu Y., Guo L., Cai P., Design and Implementation of Leak Acoustic Signal Correlator for Water Pipelines, Information Technology Journal, 12 (11), 2195-2200, 2013.
  • 20. Rajeev P., Kodikara J., Chiu W.K., Kuen T., Distributed Optical Fibre Sensors and Their Applications in Pipeline Monitoring, Key Engineering Materials, 558, 424-434, 2013.
  • 21. Ayala-Cabrera D., Herrera M., Izquierdo J., Ocaña–Levario S.J., Pérez–García R., GPR-Based Water Leak Models in Water Distribution Systems, Sensors, 13 (12), 15912-15936, 2013.
  • 22. NDE Pipeline Inspection. https://www.nde-ed.org/AboutNDT/SelectedApplications/PipelineInspection/ PipelineInspection.htm. Erişim tarihi: Ocak 21, 2017.
  • 23. Barbian O.A., Handbook Automated Ultrasonic Testing Systems-IIW Handbook, DVS-Verlag, Düsseldorf, Germany, 2008.
  • 24. Inuktun - World-class Remotely Controlled Camera Robotic Pipe Inspection Systems and Robotic Crawlers. http://www.inuktun.com/crawler-vehicles/. Erişim tarihi: Ocak 21, 2017.
  • 25. PipelineExplorerOverview.http://www.nrec.ri.cmu.edu/projects/explorer/Erişim tarihi: Ocak 21, 2017.
  • 26. Ahrary A., Tian L., Kamata S., Ishikawa M., An Autonomous Sewer Robots Navigation Based on Stereo Camera Information, 17th IEEE International Conference on Tools with Artificial Intelligence, Hong Kong-China, 634-639, November 14-16, 2005.
  • 27. Mazumdar A., Asada H.H., Pulse Width Modulation of Water Jet Propulsion Systems Using High-Speed Coanda-Effect Valves, J. Dyn. Syst. Meas. Contr., 135 (5), 051019-051019–11, 2013.
  • 28. Mechanical-Emerging Construction Technologies. http://wpvcemweb02.itap.purdue.edu/ect/links/ technologies/mechanical/SmartBall_LeakDetection.aspx. Erişim tarihi: Ocak 23, 2017.
  • 29. Parsa K., Lasky T.A., Ravani B., Design and Implementation of a Mechatronic, All-Accelerometer Inertial Measurement Unit, IEEE/ASME Trans. Mechatron., 12 (6), 640–650, 2007.
  • 30. Hao Y., Yuan W., Xie J., Shen Q., Chang H., Design and Verification of a Structure for Isolating Packaging Stress in SOI MEMS Devices, IEEE Sensors Journal, 17 (5), 1246-1254, 2017.
  • 31. Elmenreich W., Sensor Fusion in Time-Triggered Systems, Dissertation, Vienna University of Technology, Austria, 2002.
  • 32. Li C., Yang C., Wan J., Annamalai A. S., Cangelosi A., Teleoperation Control of Baxter Robot Using Kalman filter-based Sensor Fusion, Syst. Sci. Control Eng., 5 (1), 156-167, 2017.
  • 33. Zhang T., Liao Y., Attitude measure system based on extended Kalman filter for multi-rotors, Comput. Electron. Agric., 134, 19-26, 2017.
  • 34. Liu Y., Gong S., Lu Y., Estimation of Inertial/Magnetic Sensor Orientation for Human-Motion-Capture System, 2017 2nd International Conference on Control and Robotics Engineering (ICCRE), Bangkok-Thailand, 175–179, April 1-3, 2017.
  • 35. Qiu S., Wang Z., Zhao H., Qin K., Li Z., Hu H., Inertial/Magnetic Sensors Based Pedestrian Dead Reckoning by means of Multi-Sensor Fusion, Inf. Fusion, 39, 108-119, 2018.
  • 36. Bishop G., Welch G., An Introduction to the Kalman Filter, University of North Carolina SIGGRAPH 2001 course notes, ACM Inc., North Carolina-U.S.A., 2001.
  • 37. Faragher R., Understanding the Basis of the Kalman Filter Via a Simple and Intuitive Derivation Lecture Notes., IEEE Signal Process Mag., 29 (5), 128-132, 2012.
  • 38. Kuipers J.B., Quaternions and Rotation Sequences: A Primer with Applications to Orbits, Aerospace and Virtual Reality. Princeton University Press, Princeton, N.J.-U.S.A., 2002.
  • 39. Alaimo A., Comparison between Euler and Quaternion Parametrization in UAV dynamics, AIP Conference Proceedings, 1558 (1), 1228–1231, 2013.
  • 40. Jang J.S., Liccardo D., Automation of Small UAVs Using a Low Cost Mems Sensor and Embedded Computing Platform, 2006 IEEE/AIAA 25th Digital Avionics Systems Conference, Portland-Oregon-USA, 1–9, October 15-18, 2006.
Year 2017, Volume: 32 Issue: 4, 1393 - 1404, 08.12.2017
https://doi.org/10.17341/gazimmfd.369872

Abstract

References

  • 1. Dede Ö.T., Sezer M., The Application of Canadian Water Quality Index (CWQI) Model for The Assessment of Water Quality of Aksu Creek, Journal of the Faculty of Engineering and Architecture of Gazi University, 32 (3), 909-917, 2017.
  • 2. Ulaş A., Ovalı P.K., A New Approach to Concentric Circles Theory As Urban Growth Model in Concept of Physical Theories: Force Model within Kinetic and Potential Urbanization, Journal of the Faculty of Engineering and Architecture of Gazi University, 32 (2), 393-401, 2017.
  • 3. Mcneill L.S., Edwards M., Iron Pipe Corrosion in Distribution Systems, J. Am. Water Works Assn., 93 (7), 88-100, 2001.
  • 4. Alegre H., Baptista J.M., Jr E.C., Performance Indicators for Water Supply Services: Third Edition, IWA Publishing, London, United Kingdom, 2016.
  • 5. Marin P., Kingdom B., Liemberger R., The Challenge of Reducing Non-Revenue Water (Nrw) in Developing Countries - How The Private Sector Can Help : A Look at Performance-Based Service Contracting, The World Bank, 39405, December 2006.
  • 6. Hooda S.M., Rajasthan Water Assessment : Potential for Private Sector Interventions, International Finance Corporation, World Bank, New Delhi, 2017.
  • 7. Puust R., Kapelan Z., Savic D.A., Koppel T., A Review of Methods For Leakage Management in Pipe Networks, Urban Water J., 7 (1), 25-45, 2010.
  • 8. Hunaidi O., Wang A., Bracken M., Gambino T., Fricke C., Acoustic Methods for Locating Leaks in Municipal Water Pipe Networks, International Conference on Water Demand Management, Dead Sea-Jordan, 1-14, May 30- June 3, 2004.
  • 9. Sewerin AQUAPHON 200 Leak-Survey-Tool. http://muinin.com/aquaphon-a-200/. Erişim tarihi: Ocak 4, 2017.
  • 10. Lay-Ekuakille A., Griffo G., Vergallo P., Robust Algorithm Based on Decimated Padè Approximant Technique for Processing Sensor Data in Leak Detection in Waterworks, IET Sci. Meas. Technol., 7 (5), 256-264, 2013.
  • 11. Ben-Mansour R., Habib M.A., Khalifa A., Youcef-Toumi K., Chatzigeorgiou D., Computational Fluid Dynamic Simulation of Small Leaks in Water Pipelines for Direct Leak Pressure Transduction, Comput. Fluids, 57, 110-123, 2012.
  • 12. Begovich O., Pizano-Moreno A., Garcia-Malacara E., Besançon G., How Can The Temperature Affect the Performance of a Classical Pipeline Model When Plastic Pipes Are Used?, 8th International Conference on Electrical Engineering, Computing Science and Automatic Control, Merida City-Mexico, 1-6, October 26-28, 2011.
  • 13. Goh J.H., Water Pipe Leak Detection Using Electromagnetic Wave Sensor for the Water Industry, 2011 IEEE Symposium on Computers Informatics, Kuala Lumpur-Malaysia, 290-295, March 20-23, 2011.
  • 14. Lay-Ekuakille A., Vendramin G., Trotta A., Robust Spectral Leak Detection of Complex pipelines Using Filter Diagonalization Method, IEEE Sens. J., 9 (11), 1605-1614, 2009.
  • 15. Daneti M., On Using Double Power Spectral Density Information for Leak Detection, 2013 IEEE International Conference on Industrial Technology, Cape Town-Western Cape-South Africa, 1162-1167, February 25-28, 2013.
  • 16. Kadri A., Abu-Dayya A., Stefanelli R., Trinchero D., Characterization of an Acoustic Wireless Sensor for Water Leakage Detection in Underground Pipes, 2013 1st International Conference on Communications, Signal Processing and Their Applications, Sharjah-United Arab Emirates, 1-5, February 12-14 ,2013.
  • 17. Ridao P., Carreras M., Ribas D., Garcia R., Visual Inspection of Hydroelectric Dams Using an Autonomous Underwater Vehicle, J. Field Rob., 27 (6), 759-778, 2010.
  • 18. Cataldo A., Cannazza G., Benedetto E. D., Giaquinto N., A New Method for Detecting Leaks in Underground Water Pipelines, IEEE Sens. J., 12 (6), 1660-1667, 2012.
  • 19. Zhang L., Wu Y., Guo L., Cai P., Design and Implementation of Leak Acoustic Signal Correlator for Water Pipelines, Information Technology Journal, 12 (11), 2195-2200, 2013.
  • 20. Rajeev P., Kodikara J., Chiu W.K., Kuen T., Distributed Optical Fibre Sensors and Their Applications in Pipeline Monitoring, Key Engineering Materials, 558, 424-434, 2013.
  • 21. Ayala-Cabrera D., Herrera M., Izquierdo J., Ocaña–Levario S.J., Pérez–García R., GPR-Based Water Leak Models in Water Distribution Systems, Sensors, 13 (12), 15912-15936, 2013.
  • 22. NDE Pipeline Inspection. https://www.nde-ed.org/AboutNDT/SelectedApplications/PipelineInspection/ PipelineInspection.htm. Erişim tarihi: Ocak 21, 2017.
  • 23. Barbian O.A., Handbook Automated Ultrasonic Testing Systems-IIW Handbook, DVS-Verlag, Düsseldorf, Germany, 2008.
  • 24. Inuktun - World-class Remotely Controlled Camera Robotic Pipe Inspection Systems and Robotic Crawlers. http://www.inuktun.com/crawler-vehicles/. Erişim tarihi: Ocak 21, 2017.
  • 25. PipelineExplorerOverview.http://www.nrec.ri.cmu.edu/projects/explorer/Erişim tarihi: Ocak 21, 2017.
  • 26. Ahrary A., Tian L., Kamata S., Ishikawa M., An Autonomous Sewer Robots Navigation Based on Stereo Camera Information, 17th IEEE International Conference on Tools with Artificial Intelligence, Hong Kong-China, 634-639, November 14-16, 2005.
  • 27. Mazumdar A., Asada H.H., Pulse Width Modulation of Water Jet Propulsion Systems Using High-Speed Coanda-Effect Valves, J. Dyn. Syst. Meas. Contr., 135 (5), 051019-051019–11, 2013.
  • 28. Mechanical-Emerging Construction Technologies. http://wpvcemweb02.itap.purdue.edu/ect/links/ technologies/mechanical/SmartBall_LeakDetection.aspx. Erişim tarihi: Ocak 23, 2017.
  • 29. Parsa K., Lasky T.A., Ravani B., Design and Implementation of a Mechatronic, All-Accelerometer Inertial Measurement Unit, IEEE/ASME Trans. Mechatron., 12 (6), 640–650, 2007.
  • 30. Hao Y., Yuan W., Xie J., Shen Q., Chang H., Design and Verification of a Structure for Isolating Packaging Stress in SOI MEMS Devices, IEEE Sensors Journal, 17 (5), 1246-1254, 2017.
  • 31. Elmenreich W., Sensor Fusion in Time-Triggered Systems, Dissertation, Vienna University of Technology, Austria, 2002.
  • 32. Li C., Yang C., Wan J., Annamalai A. S., Cangelosi A., Teleoperation Control of Baxter Robot Using Kalman filter-based Sensor Fusion, Syst. Sci. Control Eng., 5 (1), 156-167, 2017.
  • 33. Zhang T., Liao Y., Attitude measure system based on extended Kalman filter for multi-rotors, Comput. Electron. Agric., 134, 19-26, 2017.
  • 34. Liu Y., Gong S., Lu Y., Estimation of Inertial/Magnetic Sensor Orientation for Human-Motion-Capture System, 2017 2nd International Conference on Control and Robotics Engineering (ICCRE), Bangkok-Thailand, 175–179, April 1-3, 2017.
  • 35. Qiu S., Wang Z., Zhao H., Qin K., Li Z., Hu H., Inertial/Magnetic Sensors Based Pedestrian Dead Reckoning by means of Multi-Sensor Fusion, Inf. Fusion, 39, 108-119, 2018.
  • 36. Bishop G., Welch G., An Introduction to the Kalman Filter, University of North Carolina SIGGRAPH 2001 course notes, ACM Inc., North Carolina-U.S.A., 2001.
  • 37. Faragher R., Understanding the Basis of the Kalman Filter Via a Simple and Intuitive Derivation Lecture Notes., IEEE Signal Process Mag., 29 (5), 128-132, 2012.
  • 38. Kuipers J.B., Quaternions and Rotation Sequences: A Primer with Applications to Orbits, Aerospace and Virtual Reality. Princeton University Press, Princeton, N.J.-U.S.A., 2002.
  • 39. Alaimo A., Comparison between Euler and Quaternion Parametrization in UAV dynamics, AIP Conference Proceedings, 1558 (1), 1228–1231, 2013.
  • 40. Jang J.S., Liccardo D., Automation of Small UAVs Using a Low Cost Mems Sensor and Embedded Computing Platform, 2006 IEEE/AIAA 25th Digital Avionics Systems Conference, Portland-Oregon-USA, 1–9, October 15-18, 2006.
There are 40 citations in total.

Details

Subjects Engineering
Journal Section Makaleler
Authors

Abdullah Erhan Akkaya 0000-0001-6193-5166

Muhammed Fatih Talu

Publication Date December 8, 2017
Submission Date March 9, 2017
Acceptance Date May 13, 2017
Published in Issue Year 2017 Volume: 32 Issue: 4

Cite

APA Akkaya, A. E., & Talu, M. F. (2017). Su boru hatlarında sızıntı konum tespiti için genişletilmiş kalman filtresi tabanlı IMU sensör füzyonu uygulaması. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 32(4), 1393-1404. https://doi.org/10.17341/gazimmfd.369872
AMA Akkaya AE, Talu MF. Su boru hatlarında sızıntı konum tespiti için genişletilmiş kalman filtresi tabanlı IMU sensör füzyonu uygulaması. GUMMFD. December 2017;32(4):1393-1404. doi:10.17341/gazimmfd.369872
Chicago Akkaya, Abdullah Erhan, and Muhammed Fatih Talu. “Su Boru hatlarında sızıntı Konum Tespiti için genişletilmiş Kalman Filtresi Tabanlı IMU sensör füzyonu Uygulaması”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 32, no. 4 (December 2017): 1393-1404. https://doi.org/10.17341/gazimmfd.369872.
EndNote Akkaya AE, Talu MF (December 1, 2017) Su boru hatlarında sızıntı konum tespiti için genişletilmiş kalman filtresi tabanlı IMU sensör füzyonu uygulaması. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 32 4 1393–1404.
IEEE A. E. Akkaya and M. F. Talu, “Su boru hatlarında sızıntı konum tespiti için genişletilmiş kalman filtresi tabanlı IMU sensör füzyonu uygulaması”, GUMMFD, vol. 32, no. 4, pp. 1393–1404, 2017, doi: 10.17341/gazimmfd.369872.
ISNAD Akkaya, Abdullah Erhan - Talu, Muhammed Fatih. “Su Boru hatlarında sızıntı Konum Tespiti için genişletilmiş Kalman Filtresi Tabanlı IMU sensör füzyonu Uygulaması”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 32/4 (December 2017), 1393-1404. https://doi.org/10.17341/gazimmfd.369872.
JAMA Akkaya AE, Talu MF. Su boru hatlarında sızıntı konum tespiti için genişletilmiş kalman filtresi tabanlı IMU sensör füzyonu uygulaması. GUMMFD. 2017;32:1393–1404.
MLA Akkaya, Abdullah Erhan and Muhammed Fatih Talu. “Su Boru hatlarında sızıntı Konum Tespiti için genişletilmiş Kalman Filtresi Tabanlı IMU sensör füzyonu Uygulaması”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, vol. 32, no. 4, 2017, pp. 1393-04, doi:10.17341/gazimmfd.369872.
Vancouver Akkaya AE, Talu MF. Su boru hatlarında sızıntı konum tespiti için genişletilmiş kalman filtresi tabanlı IMU sensör füzyonu uygulaması. GUMMFD. 2017;32(4):1393-404.