With rapid development in electronics and microelectromechanical systems (MEMS) technology, it becomes possible and attractive to monitor rotor dynamics by directly installing MEMS accelerometers on rotors. This paper studies the mathematical modelling of the orthogonal outputs from an on-rotor MEMS accelerometer and proposes a method to eliminate the gravitational acceleration projected on the measurement axes. This is achieved by shifting the output in the normal direction by /2 using a Hilbert transform and then combining it with the output of the tangential direction. With further compensation of the combined signal in the frequency domain, the tangential acceleration of the rotor is reconstructed to a high degree of accuracy. Experimental results show that the crankshaft tangential acceleration of a reciprocating compressor, obtained by the proposed method, can well discriminate different discharge pressures and allow common leakage faults to be detected and diagnosed for online condition monitoring.

Abstract-Planetary Gears (PG) are widely used in many important transmission systems such as helicopters and wind turbines due to its advantages of high power-weight ratio, self-centering and high transmission ratio. Vibration based condition monitoring of PG has received extensive researches for ensuring safe operations of these critical systems. However, due to the moving mesh gears and noise influences, the diagnostics of planet gear faults by conventional vibration measurements needs intensive signal processing but provides less satisfactory performance. This study investigates Instantaneous Angular Speed (IAS) based diagnostics which associates more directly with gear dynamics and is not influenced by the moving mesh gears. A pure torsional dynamic model of a PG is developed to gain the characteristics of IAS under different fault cases. Then experiments are performed to evaluate this IAS based diagnostics. Particularly, IAS signatures obtained by demodulating the frequency modulated pulse trains produced by two in-house made encoder wheels mounted at both the input and output of the PG. In addition, order spectrum analysis is applied to IAS signals to highlight fault components. IAS order spectra exhibit clear changes in the spectral amplitudes associating with different fault frequencies, showing consistent and efficient diagnostics. Besides, both the measurement system and signal processing computation for IAS based monitoring are more costeffective and easier to be implemented online, compared with conventional vibration based methods.

Abstract-Conventional accelerometers installed on housing often give out less accurate diagnostic results for planetary gearbox because the mesh excitation of planet gears change with carrier movement. Recent significant advancements in low-power and low-cost Micro-Electro-Mechanical Systems (MEMS) technologies make it possible and easier to mount MEMS accelerometers directly on the rotating shaft, enabling more accurate dynamic characteristics of the rotating machine to be acquired and used for condition monitoring. In this paper, two tiny MEMS accelerometers are installed diametrically opposite each other on the lowspeed input shaft of a planetary gearbox to measure the acceleration signals. The acceleration signals sensed by each MEMS will contain both the tangential acceleration and gravitational acceleration, but the latter can be removed by summing the acceleration signals from both sensors in order to characterise the rotor dynamics precisely. The experimental results show that the tangential acceleration measured on the low-speed input shaft of a planetary gearbox can clearly indicate faults, thus providing a reliable and lowcost method for planetary gearbox condition monitoring.

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With recent development in wireless communication and Micro Electro Mechanical Systems (MEMS) technology, it becomes easier to monitor rotating machinery conditions by mounting compact wireless MEMS accelerometers directly on the rotor. This has the potential to provide more accurate dynamic characteristics of the rotating machine and hence achieving high monitoring performance. In this paper, a tiny MEMS accelerometer together with a battery powered microcontroller is mounted on the flywheel to acquire the on-rotor accelerations of a two-stage reciprocating compressor. The measured acceleration data is streamed to a host computer wirelessly via Bluetooth Low Energy (BLE) module. The true tangential acceleration is reconstructed by combining two orthogonal outputs of the sensor, which contain gravitational accelerations. To evaluate the performance of the wireless sensor, three different fault conditions including intercooler leakage, second stage discharge valve leakage and asymmetric stator winding of the motor driver are simulated individually on the compressor test rig. To confirm the wireless sensor performance, an incremental optical encoder was installed on the compressor flywheel to acquire the Instantaneous Angular Speed (IAS) signal for comparison with signals from the wireless sensor. The experimental results show that the running status of the compressor can be remotely monitored, allowing different leakages and motor faults to be diagnosed based on the tangential acceleration reconstructed from a wireless on-rotor MEMS accelerometer.