Abstract:
Small Satellite Launch Vehicle (SSLV) is a four-stage launcher that is being developed by the
Indian Space Research Organization (ISRO) for launching small satellites and has the potential
to enable multiple orbital drop-offs. Of the four stages, three of them are solid propellant stages
that used the Flex Nozzle Control (FNC) system for controlling the deflection of the rocket
nozzle. FNC system uses Electromechanical Actuators (EMAs) for closed loop position control
in the pitch and yaw axis of SSLV.
Fault diagnosis is a critical problem in spacecraft operations in terms of performance,
safety, and reliability. Feature extraction for the generation of the dataset is done using Wavelet
Transform (WT). A fault classifier based on Wavelet Neural Network (WNN) is used for the
diagnosis of five system conditions. When compared with the conventional artificial neural
network (ANN), WNN considers the fault type comprehensively and provides more accurate
results. The modeling of launch vehicle actuation system and the fault classifier network was
evaluated in the MATLAB environment
