BridgeMon logo

Accuracy Class A(5) Achieved with SiWIM®

One of the key objectives of the BridgeMon project was to achieve a step change in accuracy and long term stability of the SiWIM® bridge weigh-in-motion system. 


SiWIM® has been used for over a decade for short-term, up to 1-month measurements in many countries around Europe, but an improvement was needed to become even more successful. Thus, testing of various approaches was carried out using numerical modelling and in-field measurements on three different bridges in Slovenia. The most successful approaches were implemented in an updated version of the software.

Free-of-Axle Detector installation, which does not require any action on the pavement, is one of the key advantages of the SiWIM® system. Improvements in axle detection algorithms and instrumentation strategies showed that the updated SiWIM® system only missed 3 of the 542 axles crossing a 20-m beam-and-slab bridge 3 of the 778 axles crossing a 6-m culvert.

A vast number of other enhancements were implemented within the system with updated algorithms for calculating the bridge influence line, calculation of vehicle weights, temperature/velocity calibration and improved approaches for quality assurance of measurements.

All improvements were verified by comparing the SiWIM® results with the re-sults of static weighing which was carried out by the police. Results of 178 freight vehicles measured over a period of 15 months on a 6-m culvert showed an improvement of four accuracy classes from class E(35) to class C(15). Despite this remarkable improvement better accuracy could not have been achieved due to bad pavement condition. The pavement was shown to be uneven, with a bump at the entry to the bridge. This demonstrated the importance of selecting a bridge with a smooth road profile.

Results of 122 freight vehicles from the 20-m beam-and-slab bridge were con-siderably better. The improved version of SiWIM® showed an increase in accu-racy from D+(20) to B(10), representing an improvement of two accuracy clas-ses. Even more promisingly, it was shown that when the lighter vehicles, which are of less interest from a traffic monitoring perspective, were omitted from the accuracy classification, the system was capable of achieving accuracy class A(5) for gross weights. This is extremely rare in WIM technology and represents a huge advancement in the field of Bridge-WIM, particularly considering that the results were achieved over 6-months long monitoring period.

The work carried out in WP1 of the BridgeMon project has lead to considerable improvements in the accuracy of the SiWIM® system and should improve the ability of Cestel to compete with other WIM technologies in the field of traffic load monitoring.

Latest News