Improved Railway Track Irregularities Classification by a Model Inversion Approach
Over time railway networks have become complex Systems characterized by manifold types of technical components with a broad range of age distribution. De facto, about 50 percent of the life cycle costs of railway infrastructures are made up by direct and indirect maintenance costs. A remedy can be provided by a condition based preventive maintenance strategy leading to an optimized scheduling of maintenance actions taking the actual aswell as the expected future infrastructure condition into account. A prerequisite is, however, that the thousands of Kilometers of railway tracks are almost continuously monitored. Thus, a promising approach is the usage of low-cost sensors, e.g. accelerometers and gyroscopes, which can be installed on common in-line freight and passenger trains. Due to ambiguous data records a credible classification of railway track irregularities directly from these data is challenging. Alternatively to this pure data-driven approach, in this paper a novel hybrid Approach is presented. To this end, a simplified vehicle Suspension model is applied for the purpose of railway track condition monitoring by analyzing the dynamic railway track - Train interactions. The inversion of the model can be used to recalculate the actual inputs (irregularities) of the monitored system (rail surface) which have caused recorded System Responses (dynamic vehicle reactions and acceleration data, respectively). These recalculated inputs are a sound Basis of subsequent data-driven condition monitoring analyses. In this preliminary study, a classification algorithm is implemented to identify a simulated railway track irregularity automatically.
System performance prognostic: context, issues and requirements
Maintenance plays now a critical role in manufacturing for achieving important cost savings and competitive advantage while preserving product and process conditions. Such a role suggests moving from conventional maintenance practices to predictive strategy. However industrial systems are complex and need to have a global view of the system health and its performance. Indeed a maintenance action has to be done at the right time according to the system performance and the component Remaining Useful Life (RUL) given by a prognostic process. Nevertheless system performance prognostic are lacking in generic methodology and support tools for assessing system performance vs. component degradations. In that way, generic concepts in relation with dysfunctional causality of the system performance are introduced. These concepts are traditionally modelled separately although they interact with each others. Thus this paper aims at giving issues and requirements on models representative of each concept and for information to share between them in order to reach a global system performance prognostic model.
Numerical and experimental investigation on air distributor design of fluidized bed reactor of sawdust pyrolysis
Abstract An improved biomass conversion in a lab-scale fluidized bed reactor (FBR) is achieved by optimizing the air distributor orifice size and number. Two approaches for introducing air were numerically and experimentally examined. These included perforated plate and downward orifice sparger. 3 mm and 5 mm orifice diameters, and 7, 9 and 13 holes were simulated at flow velocities of 2, 4, 6, and 8 times the minimum fluidization velocity, Umf. The simulation results revealed that increasing the orifice number has a positive effect on gas holdup, particularly for the perforated plate, which showed a uniform distribution of bubbles. The sparger configuration produced larger bubbles sizes, which could lead to better recirculation of solid flux, while stagnant particle zones were observed at the lower section of both distributors. A pyrolysis unit is also inserted at the top of freeboard of the FBR. For perforated plate with 6Umf, the pyrolysis process achieved thermal and cold gas efficiencies of 82.91% and 52.03%, respectively, while combustible gases with 41.6%mol CO, 8.7%mol CH 4 and 2.17%mol HC, were obtained. For sparger pipe and 6U mf _sp, 35.33 ppm NOx and 111 ppm SO 2 were measured in flue gas from combustion process at bed region.