Automated Classification of Microwave Transmitter Failures Using Virtual Sensors

Abstract

Each year, nearly $100 M is spent replacing high-power microwave tubes in the fleet. In many cases (estimated at over 25%), tubes that are operating perfectly are inadvertently replaced because there are insufficient in-situ monitoring equipment available to diagnose specific problems within the system. High-power microwave vacuum tubes used in radar or communications systems have minimal conditionbased maintenance capability and no means to identify specific component failures. This chapter presents the results from a system that uses cathode current and acoustic emission sensors combined as a virtual sensor to locate and classify microwave transmitter failures. Data will be shown which differentiate the failure mode from subsystems on a radar klystron and from a communications system magnetron. The use of the integrated condition assessment system (ICAS) to acquire and track virtual sensor data will also be described. These results offer promise of a low-cost, nonintrusive system to monitor microwave transmitters, which correctly identifies component failures avoiding incorrect replacement of high-value klystrons, magnetrons, or traveling wave tubes. This advanced technique also offers the possibility of developing built-in prognostic capabilities within the radar system to provide advanced warning of a system malfunction.