# Development and Testing of a Railway Bridge Weigh-in-Motion System
## 1 Introduction  
Today, with the general trend of increasing axle loads and operating speeds of trains, the condition of railway bridges is of greater concern, which requires more detailed analyses. These detailed assessments are even more important for old bridges, which are often subject to higher loads than originally envisaged. Furthermore, as rail markets across Europe are deregulated, track owners will have less control over train operations. To ensure compliance of train operators with the specified weight limits, simple and efficient methods of calculating train weights are required. This has led to an interest in methods of weighing trains in motion in recent years [1; 2; 3; 4]. The accurate modelling of load in bridge assessments has been increasingly recognized in research projects conducted in Europe [5; 6; 7; 8; 9], the USA [10], Canada [11; 12; 13; 14; 15], Japan [16; 17], China [18; 19], and elsewhere. Inaudi [20] has conducted an overview of 40 bridge monitoring projects carried out in the period, 1996-2010, in 13 different countries. Bridge weigh-in-motion (B-WIM), first proposed by [PERSON] in the 1970s [21], is a common technique used for road traffic load measurements in studies of this kind. While weigh-in-motion (WIM) technology [22] refers generally to the various methods of calculating axle and gross vehicle weights (GVW) of vehicles travelling at full speed, B-WIM is a method of collecting such data using measurements taken from an instrumented bridge [23]. A large body of research has been carried generated in B-WIM, resulting in commercial systems becoming available, notably the SiWIM system, adapted for use in this study [24]. Most research has been focused on B-WIM for road bridges; railway bridges have received relatively little attention [25]to date. Methods currently used for weighing trains in motion generally consist of either measuring strains directly in the rail or measuring the vertical axle forces transmitted through the rail to the sleepers and their supports. The first method allows trains to be weighed while travelling at speed. However, the usual electrical resistance strain sensors are infeasible on electrified tracks due to electrical induction surges. The second method is more accurate but requires the installation of a solid foundation under the track and that trains travel at very low speeds during measurement. The use of B-WIM technology allows for the large-scale collection of railway carriage weight data while trains are in regular service. The extension of the B-WIM concept to railway bridges was first proposed in Sweden [26]. [PERSON] and [PERSON] [27] then developed a toolbox, programmed in MATLAB, for monitoring bridge behaviour during train passage based on the algorithm developed in [26]. [PERSON] and [PERSON] [3] adopted B-WIM to weigh trains in motion on a reinforced concrete railway viaduct near Sao Luis, Brazil. [PERSON] and [PERSON] [28] implemented a B-WIM system to monitor fatigue on the Soderstrom Railway Bridge in Sweden with a reported axle load accuracy of \(\pm 15\%\) and bogie load accuracy of \(\pm 8\%\), both with \(95\%\) confidence. [PERSON] et al. [4] proposed a method for traffic characterization, adopting techniques developed by others [26; 21; 29], that describes the use of both WIM and B-WIM to estimate axle loads and the geometry of trains crossing the old Portuguese Trezoi Bridge, assuming a constant velocity during the passage of the train. In the context of B-WIM, there are significant differences between road and railway bridges. Railway bridges have the advantages of:  
* Trains being constrained to travel on the tracks--this eliminates problems that can arise due to variation in the transverse vehicle position in the lane or vehicles changing lanes on road bridges. * Railway tracks being smoother than road surfaces--trains tend to have less vehicle dynamic excitation than trucks. * Train configurations being less variable than road vehicles--making it easier to identify errors in axle detection and calculated weights.