scholarly journals High Accuracy Weigh-in-Motion Systems for Direct Enforcement

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8046
Author(s):  
Piotr Burnos ◽  
Janusz Gajda ◽  
Ryszard Sroka ◽  
Monika Wasilewska ◽  
Cezary Dolega
Keyword(s):  
Climatic Factors ◽  
High Sensitivity ◽  
High Accuracy ◽  
System Operation ◽  
Short Term ◽  
Vehicle Weight ◽  
Weigh In Motion ◽  
Moving Vehicles ◽  
Gross Vehicle Weight ◽  
Dynamic Weighing

In many countries, work is being conducted to introduce Weigh-In-Motion (WIM) systems intended for continuous and automatic control of gross vehicle weight. Such systems are also called WIM systems for direct enforcement (e-WIM). The achievement of introducing e-WIM systems is conditional on ensuring constant, known, and high-accuracy dynamic weighing of vehicles. WIM systems weigh moving vehicles, and on this basis, they estimate static parameters, i.e., static axle load and gross vehicle weight. The design and principle of operation of WIM systems result in their high sensitivity to many disturbing factors, including climatic factors. As a result, weighing accuracy fluctuates during system operation, even in the short term. The article presents practical aspects related to the identification of factors disturbing measurement in WIM systems as well as methods of controlling, improving and stabilizing the accuracy of weighing results. Achieving constant high accuracy in weighing vehicles in WIM systems is a prerequisite for their use in the direct enforcement mode. The research results presented in this paper are a step towards this goal.

Research on Integrated and Portable Weigh-in-Motion Scale

2012 ◽  
Vol 192 ◽  
pp. 149-153
Author(s):  
Liang Hao
Keyword(s):  
Data Collection ◽  
Dynamic Characteristic ◽  
Strain Gauge ◽  
High Accuracy ◽  
Traffic Data ◽  
Ansys Software ◽  
Weigh In Motion ◽  
Traffic Data Collection ◽  
Dynamic Weighing

The integrated dynamic weighing scale with a high accuracy was developed based on analyzing the loads when vehicles passed on the weighing scale. The ANSYS software was applied to determine the sensor’s foil strain gauge position and the dynamic characteristic was verified through the experiment; meanwhile the hardware and measuring software in the system were simply introduced in this article. Finally through the experiments the Weigh-In-Motion (WIM) system can be used in traffic data collection and is assistant tool for overload check.

scholarly journals Using Statistical Analysis of an Acceleration-Based Bridge Weigh-In-Motion System for Damage Detection

2020 ◽  
Vol 10 (2) ◽  
pp. 663 ◽  
Author(s):  
Eugene OBrien ◽  
Muhammad Arslan Khan ◽  
Daniel Patrick McCrum ◽  
Aleš Žnidarič
Keyword(s):  
Statistical Analysis ◽  
Damage Detection ◽  
Interaction Model ◽  
Statistical Properties ◽  
Vehicle Weight ◽  
Motion System ◽  
Weigh In Motion ◽  
Gross Vehicle Weight ◽  
Bridge Damage ◽  
Bridge Weigh In Motion

This paper develops a novel method of bridge damage detection using statistical analysis of data from an acceleration-based bridge weigh-in-motion (BWIM) system. Bridge dynamic analysis using a vehicle-bridge interaction model is carried out to obtain bridge accelerations, and the BWIM concept is applied to infer the vehicle axle weights. A large volume of traffic data tends to remain consistent (e.g., most frequent gross vehicle weight (GVW) of 3-axle trucks); therefore, the statistical properties of inferred vehicle weights are used to develop a bridge damage detection technique. Global change of bridge stiffness due to a change in the elastic modulus of concrete is used as a proxy of bridge damage. This approach has the advantage of overcoming the variability in acceleration signals due to the wide variety of source excitations/vehicles—data from a large number of different vehicles can be easily combined in the form of inferred vehicle weight. One year of experimental data from a short-span reinforced concrete bridge in Slovenia is used to assess the effectiveness of the new approach. Although the acceleration-based BWIM system is inaccurate for finding vehicle axle-weights, it is found to be effective in detecting damage using statistical analysis. It is shown through simulation as well as by experimental analysis that a significant change in the statistical properties of the inferred BWIM data results from changes in the bridge condition.

Estimation of bridge static response and vehicle weights by frequency response analysis

1998 ◽  
Vol 25 (4) ◽  
pp. 631-639 ◽  
Author(s):  
G Thater ◽  
P Chang ◽  
D R Schelling ◽  
C C Fu
Keyword(s):  
Dynamic Effect ◽  
Dynamic Responses ◽  
Response Analysis ◽  
Static Response ◽  
Actual Weight ◽  
Service Testing ◽  
Weigh In Motion ◽  
Moving Vehicles ◽  
Bridge Structures ◽  
Truck Weight

A methodology is developed to more accurately estimate the static response of bridges due to moving vehicles. The method can also be used to predict dynamic responses induced by moving vehicles using weigh-in-motion (WIM) techniques. Historically, WIM is a well-developed technology used in highway research, since it has the advantage of allowing for the stealthy automatic collection of weight data for heavy trucks. However, the lack of accuracy in determining the dynamic effect in bridges has limited the potential for its use in estimating the fatigue life of bridge structures and their components. The method developed herein amends the current WIM procedures by filtering the dynamic responses accurately using the Fast Fourier Transform (FFT). Example applications of the proposed method are shown by using computer-generated data. The method is fast and improves the predicted truck weight up to 5% of the actual weight, as compared to errors up to 10% using the current WIM methods.Key words: weigh-in-motion, digital filters, FFT, bridge dynamics, in-service testing.

Virtual Monitoring of orthotropic steel deck using bridge weigh-in-motion algorithm: Case study

2018 ◽  
Vol 18 (2) ◽  
pp. 610-620 ◽  
Author(s):  
Longwei Zhang ◽  
Hua Zhao ◽  
Eugene J OBrien ◽  
Xudong Shao
Keyword(s):  
Field Tests ◽  
Life Assessment ◽  
Dynamic Strain ◽  
Orthotropic Steel Deck ◽  
Remaining Service Life ◽  
Fatigue Life Assessment ◽  
Weigh In Motion ◽  
Gross Vehicle Weight ◽  
Bridge Weigh In Motion ◽  
Steel Deck

This article outlines a Virtual Monitoring approach for fatigue life assessment of orthotropic steel deck bridges. Bridge weigh-in-motion was used to calculate traffic loads which were then used to calculate “virtual” strains. Some of these strains were checked through long-term monitoring of dynamic strain data. Field tests, incorporating calibration with pre-weighed trucks and monitoring the response to regular traffic, were conducted at Fochen Bridge, which has an orthotropic steel deck and is located in Foshan City, China. In the calibration tests, a 45-t 3-axle truck ran repeatedly across Lane 2, the middle lane in a 3-lane carriageway. The results show that using an influence surface to weigh vehicles can improve the accuracy of the weights and, by inference, of remaining service life calculations. The most fatigue-prone position was found to be at the cutout in the diaphragms. Results show that many vehicles are overweight—the maximum gross vehicle weight recorded was 148 t, nearly 3.6 times heavier than the fatigue design truck.

scholarly journals Short- and Long-term Biologic Variability of Galectin-3 and Other Cardiac Biomarkers in Patients with Stable Heart Failure and Healthy Adults

2016 ◽  
Vol 62 (2) ◽  
pp. 360-366 ◽  
Author(s):  
Emily I Schindler ◽  
Jeffrey J Szymanski ◽  
Karl G Hock ◽  
Edward M Geltman ◽  
Mitchell G Scott
Keyword(s):  
Heart Failure ◽  
Troponin I ◽  
Prognostic Biomarker ◽  
High Sensitivity ◽  
Cardiac Biomarkers ◽  
Healthy Individuals ◽  
Short Term ◽  
Galectin 3 ◽  
Short And Long Term

Abstract BACKGROUND Galectin-3 (Gal-3) has been suggested as a prognostic biomarker in heart failure (HF) patients that may better reflect disease progression than traditional markers, including B-type natriuretic peptide (BNP) and cardiac troponins. To fully establish the utility of any biomarker in HF, its biologic variability must be characterized. METHODS To assess biologic variability, 59 patients were prospectively recruited, including 23 male and 16 female patients with stable HF and 10 male and 10 female healthy individuals. Gal-3, BNP, and high-sensitivity cardiac troponin I (hs-cTnI) were assayed at 5 time points within a 3-week period to assess short-term biologic variability. Long-term (3-month) biologic variability was assessed with samples collected at enrollment and after 4, 8, and 12 weeks. RESULTS Among healthy individuals, mean short-term biologic variability, expressed as intraindividual CV (CVI), was 4.5% for Gal-3, 29.0% for BNP, and 14.5% for hs-cTnI; long-term biologic variability was 5.5% for Gal-3, 34.7% for BNP, and 14.7% for hs-cTnI. In stable HF patients, mean short-term biologic variability was 7.1% for Gal-3, 22.5% for BNP, and 8.5% for hs-cTnI, and mean long-term biologic variability was 7.7% for Gal-3, 27.6% for BNP, and 9.6% for hs-cTnI. CONCLUSIONS The finding that Gal-3 has minimal intraindividual biological variability adds to its potential as a useful biomarker in HF patients.

Vehicle Weight Estimation Using Wireless Accelerometers on a Steel-Box Girder Bridge

2019 ◽  
Author(s):  
Tomonori Nagayama ◽  
So Kato ◽  
Haoqi Wang ◽  
Di Su ◽  
Mayuko Nishio
Keyword(s):  
Weight Estimation ◽  
Box Girder ◽  
Vehicle Weight ◽  
Efficient Management ◽  
Weigh In Motion ◽  
Speed Fluctuation ◽  
Drive Speed ◽  
Box Girder Bridge ◽  
Girder Bridge ◽  
Steel Box Girder Bridge

<p>While the traffic loads need to be understood toward efficient management of bridges, the loads on each bridge are not well assessed. An easy‐to‐implement vehicle weight estimation technique toward Bridge Weigh‐In‐Motion (BWIM) is developed based on wireless accelerometers; the algorithm is studied for the application to ordinary road bridges where traffic speed is not necessarily high and drive speed fluctuation is not insignificant. The method uses only accelerometers installed on the girders, decreasing installation cost and time which typical BWIM systems based on strain measurement need. A measurement system consisting of battery operated wireless sensors is employed. The system can continue to work over weeks to assess the vehicle weigh distributions of days of a week. The system is installed on a continuous box‐girder bridge and the performance is examined. The system was shown to assess the weight of all heavy vehicles.</p>

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