Diagnose komplexer Systeme am Beispiel eines Tank-Ballast-Systems

We consider the problem of diagnosis in complex systems with the example of tank ballast systems. It is shown that known approaches for diagnosis either restricting to quantitative or qualitative methods are not suitable. Therefore, we introduce a new approach combining quantitative and qualitative aspects. It does not renounce to complete information available in quantitative measurements as it is inevitably the case for qualitative methods that only use a classification of the measurements. Decisions for the diagnosis process however are made with the help of qualitative comparisons. Therefore, the approach is robust against noise. Finally, the performance of this new approach is demonstrated by many random tests

A simulation-based approach for railway applications using GPR

In this work a numerical model capable to predict the electromagnetic response of railway ballast aggregates under different physical conditions has been calibrated and validated by a simulation-based approach. The ballast model is based on the main physical and geometrical properties of its constituent material and it is generated by means of a random-sequential absorption (RSA) approach. A finite-difference time-domain (FDTD) simulator is then employed to calculate the ground-penetrating radar (GPR) signal response to the scenario. The calibration of the model has been performed by taking into account the main physical properties and the grain size characteristics of both the reference ballast material and a fine-grained pollutant material, namely, an A4 soil type material, according to the AASHTO soil classification. The synthetic GPR response has been generated by using the gprMax freeware simulator. Several scenarios have been considered, which in turn were reproduced in laboratory environment and used for the validation of the model. Promising results have demonstrated the high potential of such approach in characterizing the simulated response of complex coarse-grained heterogeneous materials

An intelligent framework and prototype for autonomous maintenance planning in the rail industry

This paper details the development of the AUTONOM project, a project that aims to provide an enterprise system tailored to the planning needs of the rail industry. AUTONOM extends research in novel sensing, scheduling, and decision-making strategies customised for the automated planning of maintenance activities within the rail industry. This paper sets out a framework and software prototype and details the current progress of the project. In the continuation of the AUTONOM project it is anticipated that the combination of techniques brought together in this work will be capable of addressing a wider range of problem types, offered by Network rail and organisations in different industries

Expert systems for automated maintenance of a Mars oxygen production system

A prototype expert system was developed for maintaining autonomous operation of a Mars oxygen production system. Normal operation conditions and failure modes according to certain desired criteria are tested and identified. Several schemes for failure detection and isolation using forward chaining, backward chaining, knowledge-based and rule-based are devised to perform several housekeeping functions. These functions include self-health checkout, an emergency shut down program, fault detection and conventional control activities. An effort was made to derive the dynamic model of the system using Bond-Graph technique in order to develop the model-based failure detection and isolation scheme by estimation method. Finally, computer simulations and experimental results demonstrated the feasibility of the expert system and a preliminary reliability analysis for the oxygen production system is also provided

A condition assessment approach for highway filter drains using ground penetrating radar

The deterioration of highway filter drains (HFDs) is driven by the intrusion of foreign particles within the drainage trench. Being a porous material that offers high water removal capacity at the beginning of its service life, the drainage performance of the backfill can be significantly reduced in time by the introduced fouling material. This poses a serious safety hazard for road users (standing water on the carriageway), and can potentially have an effect in the structural capacity of the pavement. With currently limited approaches to methodically evaluate the physical condition of such assets, the Ground Penetrating Radar (GPR) offers an effective, non-destructive and continuous way to achieve this at both the project and network level. The laboratory calibration study carried out to support its adoption in a condition assessment system, builds upon the evaluation of a HFD-specific condition index aligned to permeability trials and the extraction of dielectric properties of the granular backfill material at different fouled states. The paper thus discusses what kind of HFD distress information are to be collected (condition data) and how this can be achieved (data collection methods), and defines four distinctive HFD media condition bands (Excellent to Very Poor) based on the proposed free voids ratio (RVF) ranges and extracted relative permittivity values

Highway filter drains maintenance management

Across a large part of the UK highways network the carriageway and pavement foundations are drained by Highway Filter Drains (HFDs). A HFD is a linear trench constructed either at the pavement edge or central reserve, fitted with a porous carrier pipe at the base and backfilled with an initially highly porous aggregate material. This arrangement enables the swift removal of surface runoff and subsurface water from the pavement system minimising road user hazards and eliminating risk of structural damage to the pavement sub-base. The highly porous backfill filters throughout its operational life fines washed from the pavement wearing course or adjacent land. HFDs have been found to be prone to collecting near the basal sections (pipe) or surface layers contaminants or detritus that causes the filter media to gradually block. The process has been defined as HFD clogging and it has been found to lead to reduced drainage capacity and potentially severe drop of serviceability. O&M contractual agreements for DBFO projects usually propose in-service and handback requirements for all assets included in the concession portfolio. Different performance thresholds are thus prescribed for pavements, structures, ancillary assets or street lighting. Similar definitions can be retrieved for drainage assets in such agreements, and these include HFDs. Performance metrics are defined though in a generic language and residual life (a key indicator for major assets that usually drives long-term maintenance planning) is prescribed without indicative means to evaluate such a parameter. Most of pavement maintenance is carried out nowadays using proactive management thinking and engineered assessment of benefits and costs of alternative strategies (what-if scenarios). Such a proactive regime is founded upon data driven processes and asset specific ageing / renewal understanding. Within the spectrum of road management, maintenance Life Cycle Costs are usually generated and updated on an annual basis using inventory and condition data linked to a Decision Support Tool (DST). This enables the assessment and optimisation of investment requirements and projection of deterioration and of treatment impacts aligned to continuous monitoring of asset performance. Following this paradigm shift in infrastructure management, a similar structured methodology to optimise HFD maintenance planning is desired and is introduced in this thesis. The work presented enables the identification of proactive maintenance drivers and potential routes in applying a systemised HFD appraisal and monitoring system. An evaluation of Asset Management prerequisites is thus discussed linked to an overview of strategic requirements to establish such a proactive approach. The thesis identifies condition assessment protocols and focuses on developing the means to evaluate deteriorated characteristics of in service drains using destructive and non-destructive techniques. A probabilistic HFD ageing / renewal model is also proposed using Markov chains. This builds upon existing deterioration understanding and links back to current treatment options and impacts. A filter drain decision support toolkit is lastly developed to support maintenance planning and strategy generation

Application of flow cytometry in ballast water analysis - biological aspects

Ballast water may, when discharged, cause the spread of nonindigenous and potentially invasive species. International ballast water treatment regulations have accelerated the development of new methods to detect, enumerate and assess the status of organisms in the water to be discharged. Flow cytometry (FCM) is a powerful technique with a broad range of applications with the possibility for multi-parametric analysis and the potential of combining it with other techniques being two strong advantages. This review will discuss whether FCM is suitable for ballast water analysis according to international ballast water regulations, and sum up the advantages and disadvantages. It will also give an overview of available labeling techniques. Finally, a discussion on the knowledge gaps and future potential for FCM within ballast water analysis is presented.publishedVersio

Simulation and visualization platform integrated under hardware control systems for a reconfigurable process control

Simulation and visualization platform integrated under hardware control systems for a reconfigurable process control