The use of passive telemetry in rotor fault diagnosis

The sensors most commonly used for monitoring machine health are wired accelerometers because of their high performances and good stability. However, these transducers are usually large in size; require an external power source. Hence, there is a need for cheaper and reliable alternative for the conventional accelerometers. This thesis reports the development of a wireless accelerometer based on Micro-Electro-Mechanical System (MEMS) inertial sensor and off-the-shelf digital RF communication modules. It is small enough to be installed on the rotating shaft of a machine. In addition, it has a high enough resolution to be used to analyse the dynamic behaviour of rotating shaft. The wireless sensor is mounted with its sensitive axis in the tangential direction with respect to the centre of the rotor. This position allows the sensor to perform high resolution tangential acceleration measurements and nullifies the centripetal acceleration. To assist in the validation of the wireless sensor, a mathematical model was derived to simulate the vibration signals from the test rig. Experimental and simulated results both confirmed the effectiveness of the wireless sensor in detecting different degrees of misalignments and unbalance of a flexible rotor system. The wireless sensor has been confirmed to possess the capability of detecting small degrees of misalignment using the spectral amplitude of the peak at 2X running speed compared to other conventional sensors (wired accelerometers, laser vibrometers). In addition, the results of the experiment and simulation have also confirmed the capacity of the wireless sensor to detect different shaft unbalance grades at 1X running speed using spectral and order magnitudes. However, the wired sensors used for comparison failed to show any clear separation of the different grades of shaft unbalance. Moreover, it has been observed that the instantaneous angular speed (IAS) derived directly from the wireless sensor correlates well with that obtained from a shaft encoder and showed the capacity to detect the main features of rotor dynamics. An advanced algorithm has been developed to remove the gravity effect. The application of the algorithm has made the IAS computed from the wireless sensor more indicative to that obtained by a shaft encoder.