Study Of X-Ray Fluorescence (XRF) And It's Application In Aero-engine Intelligent Monitoring

XRF (X-ray fluorescence) technology, using isotope radioactive sources to eradiate materials which to be measured, produces energy spectrum through a series of installations, which is used to determine the elemental material categories. This technology has been widely used in metallurgy industry and geological exploration. In this paper it is applied into the engine intelligent monitoring, so that a new type of intelligent monitoring system could be developed.Intelligent analysis technology includes status prediction and fault diagnosis. There have many successful diagnosis reasoning and calculation methods been excogitated. In this paper it focuses on two branches of grey system theory (Gray Forecasting and Gray Relational Analysis), as well as Statistics, Artificial Immune System.Gray Forecasting, regarding the predicted system as a grey system, makes use of information known to deduce the information unknown that contain failure mode and its specialty, status and development trends. The system model, in this paper, predicts metal content in oil and the engine status with this method. Gray Relational Analysis is a new and quantitative method of grey system theory, which describes the degree of correlation between the objects and factors with relational value. The system model, analyzes relational value of concentration of various elements in oil, which is used to conclude engine condition and elemental grouping.Artificial immune system is a new type of intelligent calculation that is inspired of biological immune system. It learns and memorizes the original data models, and then, does further adjustment to memorize the different data models. Finally the models are classified and marked, the results of which are used for pattern recognition and state clustering.This study contains two parts: XRF energy spectrum processing and analysis, intelligent analysis model. For the former, its input is spectrum digital data, while its output is element concentrations. Meanwhile element concentration is the input of the latter, and the outputs of the latter are current status and prediction status of the engine. Finally, an intelligent monitoring software system of engine is developed based on the above research.