TRACKING PROGRESSIVE FRACTURE\TOWARDS RETIREMENT FOR CAUSE

ONE OF THE MOST COMMON PROBLEMS IN THE FIELDS OF SYSTEM DYNAMICS AND PATTERN RECOGNITION IS THE IDENTIFICATION OF THE DYNAMIC CHARACTERISTICS OF A SYSTEM ARE KNOWN THAN AN ACCURATE MATHERMATICAL MODEL COULD BE CONSTRUCTED AND A BETTER UNDERSTANDING OF THE BEHAVIOR OF THE SYSTEM COULD BE DEVELOPED. THIS WOULD HELP IMPROVE ITS DESIGN AND PERFORMANCE, MADE ITS IDENTIFICATION EASIER, FACILITATE INSPECTION AND NON-DESTRUCTIVE TESTING AND EVALUATION. THE MAIN OBJECTIVE OF THIS WORK IS TO DEVELOP NEW AND MORE ACCURATE DYNAMIC SYSTEM IDENTIFICATION TECHNIQUES FOR SYSTEMS WITH HIGH MODAL DENSITY. THESE AE SYSTEMS WITH MODEL FREQUENCIES CLOSE TO EACH OTHER SO THAT CONVENTIONAL IDENTIFICATION TECHNIQUES CANNOT BE APPLIED. IN THIS RESEARCH EFFORT WE PROPOSE TO CONCENTRATE ON THE DEVELOP- MENT OF THE RANDOM DECREMENT SYSTEM IDENTIFICATION TECHNIQUE. THE TECHNIQUE WILL BE DEVELOPED SO THAT IT CAN BE APPLIED TO ANY TYPE OF SYSTEM IF SUFFICIENT RESPONSE DATA ARE PROVIDED IN ANALOG OR DIGITAL FORM. POSSIBLE SOURCES OF ERROR WILL BE IDENTIFIED AND CORRECTION ALGORITHUMS WILL BE TESTED.