Design and fabrication of prototype system for early warning of impending bearing failure

A test program was conducted with the objective of developing a method and equipment for on-line monitoring of installed ball bearings to detect deterioration or impending failure of the bearings. The program was directed at the spin-axis bearings of a control moment gyro. The bearings were tested at speeds of 6000 and 8000 rpm, thrust loads from 50 to 1000 pounds, with a wide range of lubrication conditions, with and without a simulated fatigue spall implanted in the inner race ball track. It was concluded that a bearing monitor system based on detection and analysis of modulations of a fault indicating bearing resonance frequency can provide a low threshold of sensitivity

Finding patterns in student and medical office data using rough sets

Data have been obtained from King Khaled General Hospital in Saudi Arabia. In this project, I am trying to discover patterns in these data by using implemented algorithms in an experimental tool, called Rough Set Graphic User Interface (RSGUI). Several algorithms are available in RSGUI, each of which is based in Rough Set theory. My objective is to find short meaningful predictive rules. First, we need to find a minimum set of attributes that fully characterize the data. Some of the rules generated from this minimum set will be obvious, and therefore uninteresting. Others will be surprising, and therefore interesting. Usual measures of strength of a rule, such as length of the rule, certainty and coverage were considered. In addition, a measure of interestingness of the rules has been developed based on questionnaires administered to human subjects. There were bugs in the RSGUI java codes and one algorithm in particular, Inductive Learning Algorithm (ILA) missed some cases that were subsequently resolved in ILA2 but not updated in RSGUI. I solved the ILA issue on RSGUI. So now ILA on RSGUI is running well and gives good results for all cases encountered in the hospital administration and student records data.Master's These

Research on computer aided testing of pilot response to critical in-flight events

Experiments on pilot decision making are described. The development of models of pilot decision making in critical in flight events (CIFE) are emphasized. The following tests are reported on the development of: (1) a frame system representation describing how pilots use their knowledge in a fault diagnosis task; (2) assessment of script norms, distance measures, and Markov models developed from computer aided testing (CAT) data; and (3) performance ranking of subject data. It is demonstrated that interactive computer aided testing either by touch CRT's or personal computers is a useful research and training device for measuring pilot information management in diagnosing system failures in simulated flight situations. Performance is dictated by knowledge of aircraft sybsystems, initial pilot structuring of the failure symptoms and efficient testing of plausible causal hypotheses

Rule-based integrated building management systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The introduction of building management systems in large buildings have improved the control of building services and provided energy savings. However, current building management systems are limited by the physical level of integration of the building's services and the lack of intelligence provided in the control algorithms. This thesis proposes a new approach to the design and operation of building management systems using rule-based artificial intelligence techniques. The main aim of is to manage the services in the building in a more co-ordinated and intelligent manner than is possible by conventional techniques. This approach also aims to reduce the operational cost of the building by automatically tuning the energy consumption in accordance with occupancy profile of the building. A rule-based design methodology is proposed for building management systems. The design adopts the integrated structure made possible by the introduction of a common communications network for building services. The 'intelligence' is coded in the form of rules in such a way that it is both independent of any specific building description and easy to facilitate subsequent modification and addition. This is achieved using an object-oriented approach and classifying the range of data available into defined classes. The rules are divided into two knowledge-bases which are concerned with the building's control and its facilities management respectively. A wide range of rule-based features are proposed to operate on this data structure and are classified in terms of the data classes on which they operate. The concepts presented in this thesis were evaluated using software simulations, mathematical analysis and some hardware implementation. The conclusions of this work are that a rule-based building management system could provide significant enhancements over existing systems in terms of energy savings and improvements for both the building's management staff and its occupants

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

Online failure prediction in air traffic control systems

This thesis introduces a novel approach to online failure prediction for mission critical distributed systems that has the distinctive features to be black-box, non-intrusive and online. The approach combines Complex Event Processing (CEP) and Hidden Markov Models (HMM) so as to analyze symptoms of failures that might occur in the form of anomalous conditions of performance metrics identified for such purpose. The thesis presents an architecture named CASPER, based on CEP and HMM, that relies on sniffed information from the communication network of a mission critical system, only, for predicting anomalies that can lead to software failures. An instance of Casper has been implemented, trained and tuned to monitor a real Air Traffic Control (ATC) system developed by Selex ES, a Finmeccanica Company. An extensive experimental evaluation of CASPER is presented. The obtained results show (i) a very low percentage of false positives over both normal and under stress conditions, and (ii) a sufficiently high failure prediction time that allows the system to apply appropriate recovery procedures

An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

Online failure prediction in air traffic control systems

This thesis introduces a novel approach to online failure prediction for mission critical distributed systems that has the distinctive features to be black-box, non-intrusive and online. The approach combines Complex Event Processing (CEP) and Hidden Markov Models (HMM) so as to analyze symptoms of failures that might occur in the form of anomalous conditions of performance metrics identified for such purpose. The thesis presents an architecture named CASPER, based on CEP and HMM, that relies on sniffed information from the communication network of a mission critical system, only, for predicting anomalies that can lead to software failures. An instance of Casper has been implemented, trained and tuned to monitor a real Air Traffic Control (ATC) system developed by Selex ES, a Finmeccanica Company. An extensive experimental evaluation of CASPER is presented. The obtained results show (i) a very low percentage of false positives over both normal and under stress conditions, and (ii) a sufficiently high failure prediction time that allows the system to apply appropriate recovery procedures

Space station automation of common module power management and distribution

The purpose is to automate a breadboard level Power Management and Distribution (PMAD) system which possesses many functional characteristics of a specified Space Station power system. The automation system was built upon 20 kHz ac source with redundancy of the power buses. There are two power distribution control units which furnish power to six load centers which in turn enable load circuits based upon a system generated schedule. The progress in building this specified autonomous system is described. Automation of Space Station Module PMAD was accomplished by segmenting the complete task in the following four independent tasks: (1) develop a detailed approach for PMAD automation; (2) define the software and hardware elements of automation; (3) develop the automation system for the PMAD breadboard; and (4) select an appropriate host processing environment