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"Nothing on the road axle detection system using direct strain measurements – A case study" presented at CERI2018 by Farhad Huseynov

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This paper proposes a new axle detection methodology using direct strain measurements. Initially, numerical analyses are carried out on a 1-D simply supported bridge structure to investigate the strain response of a bridge to a 2-axle moving vehicle. The strain response obtained from the numerical model is further studied and a new axle detection strategy, based on the second derivative of strain with respect to time, is proposed. Having developed the theoretical concept, field testing is carried out on a single span simply supported railway bridge to validate the proposed methodology and test its robustness of on a full-scale bridge.

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"Nothing on the road axle detection system using direct strain measurements – A case study" presented at CERI2018 by Farhad Huseynov

  1. 1. Workshop CERI, UCD, Dublin Wednesday 29th August 2018
  2. 2. Farhad Huseynov, Eugene OBrien, James Brownjohn, David Hester, Karen Faulkner Nothing On the Road Axle Detection System Using Direct Strain Measurements – A Case Study
  3. 3. Outline • Importance of axle detection and available systems • Analytical Study - Theoretical Basis • Experimental Validation - Field Testing • Results and Discussion
  4. 4. Axle Detection Systems • Why Important? • Bridge Weigh-In-Motion systems use axle detectors to detect axles. • Indispensable part of Bridge WIM - directly affecting accuracy of weight predictions
  5. 5. Axle Detection Systems • Traditional Axle Detection systems usually use pneumatic tubes • Requires road closures for installation and maintenance • Durability issues – exposed to traffic
  6. 6. Axle Detection Systems • State-of-the-art axle detection systems now use strain transducers to detect axles
  7. 7. Axle Detection Systems • Measure local strain response Strain response to (5-Axle Truck) Axle 1 Axle 2 Tridem
  8. 8. Axle Detection Systems • Great advantages • no need for road closures for installation or maintenance • reduced congestion, improved safety
  9. 9. Axle Detection Systems • However, have some limitations; • Effectiveness of these slab sensors depends on where the wheel is, overhead • Fail to identify presence of axles if the load is directly applied on the main girders • Limited to certain bridge types i.e. short span, integral bridges etc.
  10. 10. Objective • Overcoming these existing shortfalls in literature is the main objective of the proposed work • A new axle detection methodology is proposed which is based on the second derivative of the strain measurements with respect to time
  11. 11. Theoretical Basis 3.5t 3.5t 2.6m V=4m/s E=210 GPa I= 1.23 x 109 mm2 Methodology is based on The 2nd derivative of the strain signal with respect to time
  12. 12. Theoretical Basis Function of Strain(t) is 1st order conditional polynomial 1st derivative of Strain(t) function Signals are always continuous constant discontinuous function Not differentiable!!!
  13. 13. 2nd derivative of Strain(t) function • Positive peaks: axles arrive and leave bridge • Negative peaks: axles arrive at the sensor location 1st derivative of Strain(t) function constant discontinuous function Not differentiable!!! Signals are always continuous Theoretical Basis
  14. 14. Field Testing
  15. 15. Field Testing
  16. 16. Field Testing British Class 115 Diesel Multiple Unit (DMU) Consists of three sets: • 2 x Driving Motor Brake Second (DMBS) • 1 x Trailer Composite with Lavatory (TCL) type carriage Axle spacing in a bogie = 2.6m 12 axles in total
  17. 17. Results & Discussion
  18. 18. Theoretical Basis • Magnitudes of peaks are small 3.5t 3.5t 2.6m V=4m/s
  19. 19. Results & Discussion
  20. 20. The TRUSS ITN project (http://trussitn.eu) has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 642453 Thanks for your attention

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