Intercomparison of aircraft instruments on board the C-130 and Falcon-20 over southern Germany during EXPORT2000

In the summer 2000 EXPORT aircraft campaign (European eXport of Precursors and Ozone by long-Range Transport), two comprehensively instrumented research aircraft measuring a variety of chemical species flew wing tip to wing tip for a period of one and a quarter hours. During this interval a comparison was undertaken of the measurements of nitrogen oxide (NO), odd nitrogen species (NOy), carbon monoxide (CO) and ozone (O3). The comparison was performed at two different flight levels, which provided a 10-fold variation in the concentrations of both NO (10 to 1000 parts per trillion by volume (pptv)) and NOy (200 to over 2500 pptv). Large peaks of NO and NOy observed from the Falcon 20, which were at first thought to be from the exhaust of the C-130, were also detected on the 4 channel NOxy instrument aboard the C-130. These peaks were a good indication that both aircraft were in the same air mass and that the Falcon 20 was not in the exhaust plume of the C-130. Correlations and statistical analysis are presented between the instruments used on the two separate aircraft platforms. These were found to be in good agreement giving a high degree of correlation for the ambient air studied. Any deviations from the correlations are accounted for in the estimated inaccuracies of the instruments. These results help to establish that the instruments aboard the separate aircraft are reliably able to measure the corresponding chemical species in the range of conditions sampled and that data collected by both aircraft can be co-ordinated for purposes of interpretation.

The SAFEE on-board threat detection system

Under the framework of the European Union Funded SAFEE project(1), this paper gives an overview of a novel monitoring and scene analysis system developed for use onboard aircraft in spatially constrained environments. The techniques discussed herein aim to warn on-board crew about pre-determined indicators of threat intent (such as running or shouting in the cabin), as elicited from industry and security experts. The subject matter experts believe that activities such as these are strong indicators of the beginnings of undesirable chains of events or scenarios, which should not be allowed to develop aboard aircraft. This project aimes to detect these scenarios and provide advice to the crew. These events may involve unruly passengers or be indicative of the precursors to terrorist threats. With a state of the art tracking system using homography intersections of motion images, and probability based Petri nets for scene understanding, the SAFEE behavioural analysis system automatically assesses the output from multiple intelligent sensors, and creates. recommendations that are presented to the crew using an integrated airborn user interface. Evaluation of the system is conducted within a full size aircraft mockup, and experimental results are presented, showing that the SAFEE system is well suited to monitoring people in confined environments, and that meaningful and instructive output regarding human actions can be derived from the sensor network within the cabin.

Fusing data-mining and knowledge elicitation for the supervisory control of an aluminium plate mill

Knowledge-elicitation is a common technique used to produce rules about the operation of a plant from the knowledge that is available from human expertise. Similarly, data-mining is becoming a popular technique to extract rules from the data available from the operation of a plant. In the work reported here knowledge was required to enable the supervisory control of an aluminium hot strip mill by the determination of mill set-points. A method was developed to fuse knowledge-elicitation and data-mining to incorporate the best aspects of each technique, whilst avoiding known problems. Utilisation of the knowledge was through an expert system, which determined schedules of set-points and provided information to human operators. The results show that the method proposed in this paper was effective in producing rules for the on-line control of a complex industrial process.

Design, implementation and testing of an intelligent knowledge-based system for the supervisory control of a hot rolling mill

This paper describes the design, implementation and testing of an intelligent knowledge-based supervisory control (IKBSC) system for a hot rolling mill process. A novel architecture is used to integrate an expert system with an existing supervisory control system and a new optimization methodology for scheduling the soaking pits in which the material is heated prior to rolling. The resulting IKBSC system was applied to an aluminium hot rolling mill process to improve the shape quality of low-gauge plate and to optimise the use of the soaking pits to reduce energy consumption. The results from the trials demonstrate the advantages to be gained from the IKBSC system that integrates knowledge contained within data, plant and human resources with existing model-based systems. (c) 2005 Elsevier Ltd. All rights reserved.