Weigh-in-Motion Sensor and Controller Operation and Performance Comparison
2018-01
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Weigh-in-Motion Sensor and Controller Operation and Performance Comparison
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2018-01
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Minnesota Department of Transportation
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This research project utilized statistical inference and comparison techniques to compare the performance of different Weigh-in-Motion (WIM) sensors. First, we analyzed test-vehicle data to perform an accuracy check of the results reported by the sensor-vendor Intercomp. The results reported by Intercomp mostly matched with our own analysis, but the data were found to be insufficient to reach any conclusions about the accuracy of the sensor under different temperature and speed conditions. Second, based on the limited data from the Intercomp and IRD sensor systems, we performed tests of self-consistency and comparisons of measurements to inform the selection of a superior system. Intercomp sensor data were found to be not self-consistent but IRD data were. Given the different measurements provided by the two sensors, without additional data, we were not able to reach a conclusion regarding the relative accuracy or the duration of consistent observations before needing recalibration. Initial comparisons indicated potential problems with the Intercomp sensor. We then suggested alternate approaches that MNDOT could use to determine whether recalibration was required. Finally, we analyzed ten-month data from the IRD WIM system and four-month data from the Kistler WIM system to evaluate relative sensor accuracy. While both systems were found to be self-consistent within the data time frame, the Kistler system generated more errors than the IRD system. Conclusions regarding relative accuracy could not be reached without additional data. We identified the sorts of measurements that would need to be monitored for recalibration and the methodology needed for estimating future recalibration time.
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Gupta, Diwakar; Tang, Xiaoxu; Yuan, Lu. (2018). Weigh-in-Motion Sensor and Controller Operation and Performance Comparison. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/195172.
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