Qualitative Supervision of Naval Diesel Engine Turbocharger Systems

FAC Intelligent Components and Instruments for Control Applications, Malaga, Spain, 1992This paper presents a qualitative model the diesel engine turbocharger system of a ship. The paper also shows how qualitative models can be use for an intelligent monitoring of the process concerned

Development of an integrated remote monitoring technique and its application to para-stressing bridge system

Bridge monitoring system via information technology is capable of providing more accurate knowledge of bridge performance characteristics than traditional strategies. This paper describes not only an integrated Internet monitoring system that consists of a stand-alone monitoring system (SMS) and a Web-based Internet monitoring system (IMS) for bridge maintenance but also its application to para-stressing bridge system as an intelligent structure. IMS, as a Web-based system, is capable of addressing the remote monitoring by introducing measuring information derived from SMS into the system through Internet or intranet connected by either PHS or LAN. Moreover, the key functions of IMS such as data management system, condition assessment, and decision making with the proposed system are also introduced in this paper. Another goal of this study is to establish the framework of a para-stressing bridge system which is an intelligent bridge by integrating the bridge monitoring information into the system to control the bridge performance automatically.Peer ReviewedPostprint (published version

Intelligent flight control systems

The capabilities of flight control systems can be enhanced by designing them to emulate functions of natural intelligence. Intelligent control functions fall in three categories. Declarative actions involve decision-making, providing models for system monitoring, goal planning, and system/scenario identification. Procedural actions concern skilled behavior and have parallels in guidance, navigation, and adaptation. Reflexive actions are spontaneous, inner-loop responses for control and estimation. Intelligent flight control systems learn knowledge of the aircraft and its mission and adapt to changes in the flight environment. Cognitive models form an efficient basis for integrating 'outer-loop/inner-loop' control functions and for developing robust parallel-processing algorithms

An Intelligent Fuse-box for use with Renewable Energy Sources integrated within a Domestic Environment

This paper outlines a proposal for an intelligent fuse-box that can replace existing fuse-boxes in a domestic context such that a number of renewable energy sources can easily be integrated into the domestic power supply network, without the necessity for complex islanding and network protection. The approach allows intelligent control of both the generation of power and its supply to single or groups of electrical appliances. Energy storage can be implemented in such a scheme to even out the power supplied and simplify the control scheme required, and environmental monitoring and load analysis can help in automatically controlling the supply and demand profiles for optimum electrical and economic efficiency. Simulations of typical scenarios are carried out to illustrate the concept in operation

Implementing intelligent asset management systems (IAMS) within an industry 4.0 manufacturing environment

9th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2019; Berlin; Germany; 28 August 2019 through 30 August 2019. Publicado en IFAC-PapersOnLine 52(13), p. 2488-2493This paper aims to define the different considerations and results obtained in the implementation in an Intelligent Maintenance System of a laboratory designed based on basic concepts of Industry 4.0. The Intelligent Maintenance System uses asset monitoring techniques that allow, on-line digital modelling and automatic decision making. The three fundamental premises used for the development of the management system are the structuring of information, value identification and risk management

WSN and RFID integration to support intelligent monitoring in smart buildings using hybrid intelligent decision support systems

The real time monitoring of environment context aware activities is becoming a standard in the service delivery in a wide range of domains (child and elderly care and supervision, logistics, circulation, and other). The safety of people, goods and premises depends on the prompt reaction to potential hazards identified at an early stage to engage appropriate control actions. This requires capturing real time data to process locally at the device level or communicate to backend systems for real time decision making. This research examines the wireless sensor network and radio frequency identification technology integration in smart homes to support advanced safety systems deployed upstream to safety and emergency response. These systems are based on the use of hybrid intelligent decision support systems configured in a multi-distributed architecture enabled by the wireless communication of detection and tracking data to support intelligent real-time monitoring in smart buildings. This paper introduces first the concept of wireless sensor network and radio frequency identification technology integration showing the various options for the task distribution between radio frequency identification and hybrid intelligent decision support systems. This integration is then illustrated in a multi-distributed system architecture to identify motion and control access in a smart building using a room capacity model for occupancy and evacuation, access rights and a navigation map automatically generated by the system. The solution shown in the case study is based on a virtual layout of the smart building which is implemented using the capabilities of the building information model and hybrid intelligent decision support system.The Saudi High Education Ministry and Brunel University (UK

Intelligent monitoring and diagnosis systems for the Space Station Freedom ECLSS

Specific activities in NASA's environmental control and life support system (ECLSS) advanced automation project that is designed to minimize the crew and ground manpower needed for operations are discussed. Various analyses and the development of intelligent software for the initial and evolutionary Space Station Freedom (SSF) ECLSS are described. The following are also discussed: (1) intelligent monitoring and diagnostics applications under development for the ECLSS domain; (2) integration into the MSFC ECLSS hardware testbed; and (3) an evolutionary path from the baseline ECLSS automation to the more advanced ECLSS automation processes