FAULT DETECTION IN HEAVY DUTY WHEELS BY ADVANCED VIBRATION PROCESSING TECHNIQUES AND NUMERICAL MODELLING

The research work reported in this thesis aims at developing a methodology and a procedure for the condition monitoring and diagnostics of heavy-duty wheels based on vibration measurements at the end of the production line. The early detection of manufacturing anomalies is necessary to sensibly reduce the time/money lost due to possible problems that can rise up during the operating phases. Heavy-duty wheels are used in applications as automatic vehicles and motor trucks and are mainly composed of a polyurethane tread glued to a cast iron hub. The adhesive application between tread and hub is the most critical assembly phase, since it is completely made by an operator and a contamination of the link area between polyurethane and cast iron may happen. Furthermore the presence of rust on the hub surface can contribute to worsen the adherence interface and to reduce the operating life. As the author is aware, studies by other researchers concerning the fault detection in heavy-duty wheels are not present in literature. In order to develop a detection procedure, several wheels with different types of faults have been manufactured “ad hoc” with anomalies similar to real ones. Such anomalies consist of incorrectly adherence zones between tread and hub as well as localized or distributed rust on the hub surface. Numerous experimental tests have been carried out in order to identify the vibration effects of these defects as a function of fault type and dimensions. The thesis concerns the detection and diagnostic capability of different vibration processing techniques using well-suited indicators and determining pass/fail decision thresholds through the Tukey’s non-statistical method. Contemporary, an accurate dynamic analysis of this mechanical system has been conducted - both experimentally through modal analysis techniques and numerically through finite element method - in order to establish the influence of the dynamic properties of the system components (namely heavy-duty wheel, support, frame of the test set up) on the measured vibratory signal. Based on this dynamic characterization, a multibody model of the system has been developed: the heavy-duty wheel is considered as rigid and the yielding part is focused in the contact patch between wheel and drum. A non-linear elastic contact algorithm is adopted, based on stiffness properties previously extracted from static tests conducted on both material specimens and complete components. The model makes it possible to reproduce the vibration effects of the defects and to simulate signal modifications due to different component materials and design. as Synchronous Average and Cyclostationarity Analysis

Identifying efficient Nitrate reduction strategies in the Upper Danube

Nitrogen losses in the form of Nitrate (N-NO3) from point and diffuse sources of pollution are recognized to be the leading cause of water body impairment throughout Europe. Implementation of conservation programs is perceived as being crucial for restoring and protecting the good ecological status of freshwater bodies. The success of conservation programs depends on the efficient identification of management solutions with respect to the envisaged environmental and economic objectives. This is a complex task, especially considering that costs and effectiveness of conservation strategies depend on their locations. We applied a multi-objective, spatially explicit analysis tool, the R-SWAT-DM framework, to search for efficient, spatially-targeted solution of Nitrate abatement in the Upper Danube Basin. The Soil Water Assessment Tool (SWAT) model served as the nonpoint source pollution estimator for current conditions as well as for scenarios with modified agricultural practices and waste water treatment upgrading. A spatially explicit optimization analysis that considered point and diffuse sources of Nitrate was performed to search for strategies that could achieve largest pollution abatement at minimum cost. The set of optimal spatial conservation strategies identified in the Basin indicated that it could be possible to reduce Nitrate loads by more than 50% while simultaneously provide a higher income

On the use of Vibration Signal Analysis for Industrial Quality Control: Part I

Vibration signals can be successfully captured and analyzed for quality control at the end of the production line. Various signal processing techniques and their applications are presented in this paper. These applications demonstrate the importance of selecting proper signal processing tools in order to extract the most reliable information from the signals. The presented applications regards tooth fault detection in helical gears and the detection of assembly faults in diesel engines by means of cold test technology

Comparing calibrated parameter sets of the SWAT model for theScandinavian and Iberian peninsulas

Different SWAT models have been set-up to predict water discharge at the European scale, applying an innovative modelling protocol that involves sensitivity analysis, multi-variable calibration and regionalization of the calibrated parameters. In this application, two large regions have been considered: the Scandinavian and the Iberian peninsulas, with the main objectives: (a) to study the spatial variation of calibrated parameter sets obtained for selected sub-basins, and (b) identification of the most relevant hydrological processes in each region. The results of the analysis highlight that snow processes are dominant in Scandinavia; groundwater processes are significant in both the Scandinavian and Iberian peninsulas, while lateral flow is not significant in either region. Calibrated soil hydraulic parameters have different ranges of values in each region, reflecting a difference in runoff-generating mechanisms between the two studied regions. The contribution of this analysis is the assessment of the main differences between hydrological processes across Europe and understanding of the major transport pathways for pollutants

Regional scale hydrologic modeling of a karst-dominant geomorphology: the case study of the Island of Crete

Summarization: Crete Island (Greece) is a karst dominated region that faces limited water supply and increased seasonal demand, especially during summer for agricultural and touristic uses. In addition, due to the mountainous terrain, interbasin water transfer is very limited. The resulting water imbalance requires a correct quantification of available water resources in view of developing appropriate management plans to face the problem of water shortage. The aim of this work is the development of a methodology using the SWAT model and a karst-flow model (KSWAT, Karst SWAT model) for the quantification of a spatially and temporally explicit hydrologic water balance of karst-dominated geomorphology in order to assess the sustainability of the actual water use. The application was conducted in the Island of Crete using both hard (long time series of streamflow and spring monitoring stations) and soft data (i.e. literature information of individual processes). The KSWAT model estimated the water balance under normal hydrological condition as follows: 6400 Mm3/y of precipitation, of which 40% (2500 Mm3/y) was lost through evapotranspiration, 5% was surface runoff and 55% percolated into the soil contributing to lateral flow (2%), and recharging the shallow (9%) and deep aquifer (44%). The water yield was estimated as 22% of precipitation, of which about half was the contribution from spring discharges (9% of precipitation). The application of the KSWAT model increased our knowledge about water resources availability and distribution in Crete under different hydrologic conditions. The model was able to capture the hydrology of the karst areas allowing a better management and planning of water resources under scarcity.Presented on: Journal of Hydrolog