65,736 research outputs found
Comparison of different classification algorithms for fault detection and fault isolation in complex systems
Due to the lack of sufficient results seen in literature, feature extraction and classification methods of hydraulic systems appears to be somewhat challenging. This paper compares the performance of three classifiers (namely linear support vector machine (SVM), distance-weighted k-nearest neighbor (WKNN), and decision tree (DT) using data from optimized and non-optimized sensor set solutions. The algorithms are trained with known data and then tested with unknown data for different scenarios characterizing faults with different degrees of severity. This investigation is based solely on a data-driven approach and relies on data sets that are taken from experiments on the fuel system. The system that is used throughout this study is a typical fuel delivery system consisting of standard components such as a filter, pump, valve, nozzle, pipes, and two tanks. Running representative tests on a fuel system are problematic because of the time, cost, and reproduction constraints involved in capturing any significant degradation. Simulating significant degradation requires running over a considerable period; this cannot be reproduced quickly and is costly
Virtuality in human supervisory control: Assessing the effects of psychological and social remoteness
Virtuality would seem to offer certain advantages for human supervisory control. First, it could provide a physical analogue of the 'real world' environment. Second, it does not require control room engineers to be in the same place as each other. In order to investigate these issues, a low-fidelity simulation of an energy distribution network was developed. The main aims of the research were to assess some of the psychological concerns associated with virtual environments. First, it may result in the social isolation of the people, and it may have dramatic effects upon the nature of the work. Second, a direct physical correspondence with the 'real world' may not best support human supervisory control activities. Experimental teams were asked to control an energy distribution network. Measures of team performance, group identity and core job characteristics were taken. In general terms, the results showed that teams working in the same location performed better than team who were remote from one another
Internal combustion engine sensor network analysis using graph modeling
In recent years there has been a rapid development in technologies for smart monitoring applied to many different areas (e.g. building automation, photovoltaic systems, etc.). An intelligent monitoring system employs multiple sensors distributed within a network to extract useful information for decision-making. The management and the analysis of the raw data derived from the sensor network includes a number of specific challenges still unresolved, related to the different communication standards, the heterogeneous structure and the huge volume of data.
In this paper we propose to apply a method based on complex network theory, to evaluate the performance of an Internal Combustion Engine. Data are gathered from the OBD sensor subset and from the emission analyzer. The method provides for the graph modeling of the sensor network, where the nodes are represented by the sensors and the edge are evaluated with non-linear statistical correlation functions applied to the time series pairs.
The resulting functional graph is then analyzed with the topological metrics of the network, to define characteristic proprieties representing useful indicator for the maintenance and diagnosis
Identifying Critical Components During information Security Evaluations
Electronic communications devices intended for government or military applications must be rigorously evaluated to ensure that they maintain data confidentiality. High-grade information security evaluations require a detailed analysis of the device’s design, to determine how it achieves necessary security functions. In practice, such evaluations are labour-intensive and costly, so there is a strong incentive to find ways to make the process more efficient. In this paper we show how well-known concepts from graph theory can be applied to a device’s design to optimise information security evaluations. In particular, we use end-to-end graph traversals to eliminate components that do not need to be evaluated at all, and minimal cutsets to identify the smallest group of components that needs to be evaluated in depth
Diagnostic tolerance for missing sensor data
For practical automated diagnostic systems to continue functioning after failure, they must not only be able to diagnose sensor failures but also be able to tolerate the absence of data from the faulty sensors. It is shown that conventional (associational) diagnostic methods will have combinatoric problems when trying to isolate faulty sensors, even if they adequately diagnose other components. Moreover, attempts to extend the operation of diagnostic capability past sensor failure will necessarily compound those difficulties. Model-based reasoning offers a structured alternative that has no special problems diagnosing faulty sensors and can operate gracefully when sensor data is missing
A knowledge base architecture for distributed knowledge agents
A tuple space based object oriented model for knowledge base representation and interpretation is presented. An architecture for managing distributed knowledge agents is then implemented within the model. The general model is based upon a database implementation of a tuple space. Objects are then defined as an additional layer upon the database. The tuple space may or may not be distributed depending upon the database implementation. A language for representing knowledge and inference strategy is defined whose implementation takes advantage of the tuple space. The general model may then be instantiated in many different forms, each of which may be a distinct knowledge agent. Knowledge agents may communicate using tuple space mechanisms as in the LINDA model as well as using more well known message passing mechanisms. An implementation of the model is presented describing strategies used to keep inference tractable without giving up expressivity. An example applied to a power management and distribution network for Space Station Freedom is given
Some Obstacles to Applying the Principle of Individual Responsibility for Illness in the Rationing of Medical Services
Lately, more and more authors have asserted their belief that one of the criteria which, together with the medical ones, can and should be applied in the policy of selecting and/or prioritizing the patients in need for the allocation of medical resources with limited availability, is the principle of individual responsibility for illness. My intention in this study is to highlight some very serious obstacles looming against the attempt to apply this principle in the distribution of the medical services with limited availability. Although there are numerous such obstacles, I shall only discuss five of them (the most important, in my opinion). These are: 1) the impossibility to establish with certainty whether a patient got ill due to his lifestyle; 2) the lack of a feasible and reliable method of establishing an individual’s responsibility for his lifestyle; 3) a patient’s right to privacy; 4) some moral requirements and principles and, last but not least, 5) the ethics of the medical profession
Energy rating of a water pumping station using multivariate analysis
Among water management policies, the preservation and the saving of energy demand in water supply and treatment systems play key roles. When focusing on energy, the customary metric to determine the performance of water supply systems is linked to the definition of component-based energy indicators. This approach is unfit to account for interactions occurring among system elements or between the system and its environment. On the other hand, the development of information technology has led to the availability of increasing large amount of data, typically gathered from distributed sensor networks in so-called smart grids. In this context, data intensive methodologies address the possibility of using complex network modeling approaches, and advocate the issues related to the interpretation and analysis of large amount of data produced by smart sensor networks.
In this perspective, the present work aims to use data intensive techniques in the energy analysis of a water management network.
The purpose is to provide new metrics for the energy rating of the system and to be able to provide insights into the dynamics of its operations. The study applies neural network as a tool to predict energy demand, when using flowrate and vibration data as predictor variables
Justice and predictability in torts
Recent reexaminations of the principles of tort liability have entertained two possible
rationales for the fault principle, one "moral" and the other economic. Neither is satisfactory.
I propose here a third rationale and show how it suffices to refute at least some of the
challenges to the negligence system. The character of this rationale is causal, and the central
thesis of this paper is that in as much as the tort system should aim to place the costs of
accidents on the source of those accidents, then we have not yet found an acceptable
alternative to the negligence system. This thesis is defended and developed through a
reexamination of some recent theories of strict liability and reflection on some of what has
been said about the role of causation in torts. A backdrop to the entire discussion is the
question of how one might best ensure that potential defendants will be able to predict with
reasonable certainty which courses of action will make them liable, should damages ensue
- …