INVESTIGATION OF DYNAMIC RESPONSES OF ON-ROTOR WIRELESS SENSORS FOR CONDITION MONITORING OF ROTATING MACHINES

The most common sensors that are used to monitor the condition of a machine health are wired accelerometers. The big advantages of using these types of accelerometers are their high performance and good stability. However, they have certain drawbacks as well. These accelerometers are large in size and require a cable for external power source. Hence a more reliable and cheaper alternatives of these conventional accelerometers are needed that can eliminate the drawbacks of the wired accelerometers. This thesis reports the application of wireless Micro-Electro-Mechanical System (MEMS) accelerometer for machinery condition monitoring. These sensors are so small that they can be easily mounted on the rotating machine parts and can acquire dynamic information very accurately. One critical problem in using an on-rotor accelerometer is to extract the true tangential acceleration from the MEMS outputs. In this research, the mathematical model of an on-rotor triaxial MEMS accelerometer output signals is studied, and methods to eliminate the gravitational effect projected on X-axis (tangential direction) are proposed. The true tangential acceleration that correlates to the instantaneous angular speed (IAS) is reconstructed by combining two orthogonal outputs from the sensor that also contain gravitational accelerations. To provide more accurate dynamic characteristics of the rotating machine and hence achieving high-performance monitoring, a tiny MEMS accelerometer (AX3 data logger) has been used to obtain the on-rotor acceleration data for monitoring a two-stage reciprocating compressor (RC) based on the reconstruction of instantaneous angular speed (IAS). The findings from the experiments show that the conditions of the RC can be monitored and different faults can be identified using only one on-rotor MEMS accelerometer installed on compressor’ flywheel. In addition, the data collection method is improved by considering the wireless data transmission technique which enables online condition monitoring of the compressor. Thus, a wireless MEMS accelerometer node is mounted on the RC to measure the on-rotor acceleration signals. The node allows the measured acceleration data to be streamed to a remote host computer via Bluetooth Low Energy (BLE) module. In addition, the device is miniaturised so that can be conveniently mounted on a rotating rotor and can be driven by a battery powered microcontroller. To benchmark the wireless sensor performance, an incremental optical encoder was installed on the compressor flywheel to acquire the instantaneous angular speed (IAS) signal. Furthermore, conventional accelerometer mounted on the machine’s housing provide lower accuracy in diagnosis the faults for planetary gearboxes because of the planet gears’ varying mesh excitation due to its carrier movement. In contrast, installation of the smaller AX3 MEMS accelerometers is done at diametrically opposite direction to the each other of the planetary gearbox’s low-speed input shaft, allowing measurement of the acceleration signals which are used for condition monitoring of the gearbox. The findings from the experiments demonstrate that when tangential acceleration is measured at the planetary gearbox’s low-speed input shaft, effective fault identification is possible, offering reliability and economy in monitoring the health of planetary gearboxes

Performance evaluation of wireless MEMS accelerometer for reciprocating compressor condition monitoring

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

Diagnosis of Compound Faults in Reciprocating Compressors Based on Modulation Signal Bispectrum of Current Signals

This paper studies induction motor current signatures to detect and di-agnose faults of a two-stage reciprocating compressor (RC) which creates a varying load to the motor. It also examines the influences of stator winding faults on differ-ent common faults of the compressor. Both the conventional spectrum analysis and the state of the art modulation signal bispectrum (MSB) analysis are used to process the current signals for attaining an accurate characterisation of the modulation in-duced by the variable loads and thereby developing reliable diagnostic features. The experimental studies examine different RC faults including valve leakage, inter-cooler leakage, stator asymmetries and their compounds. The results demonstrated that the MSB has a better performance in differentiating spectrum amplitudes caused by different faults especially the compound fault. Thus the MSB based fea-tures are demonstrated to be more reliable and accurate as the analysis techniques for motor current based diagnostics

Planetary Gearbox Fault Diagnosis Using an On-Rotor MEMS Accelerometer

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

Application of Wavelet Packet Transform and Envelope Analysis to Non-stationary Vibration Signals For Fault Diagnosis of a Reciprocating Compressor

Reciprocating compressors play a major role in manufacturing industries such as oil and gas refineries, petrochemical industrial plants, etc. Therefore, it is necessary to implement online condition monitoring for early and accurate detection of faults which if not controlled can lead to machine inefficiency, damage, or total system shutdown. This paper presents the application of wavelet packet transform (WPT) and envelope analysis to non-stationary vibration signal from a two-stage reciprocating compressor for fault diagnostics. Vibration signal measured on the reciprocating compressor consist of a series of impulsive events with non-stationary random characteristics, which result mostly from mechanical impacts of the valves and impulsive fluid excitation of high-pressure turbulent flows. To characterize such vibration signal, WPT is employed to decompose the measured signal for the extraction of time-frequency information. With the help of statistical based analysis, the most optimal terminal node of the wavelet packet is selected for further study. Envelope spectrum of the optimal terminal node is processed and used for the classification of three common faults including intercooler leakage, second-stage discharge valve leakage and a combined fault at five critical tank discharge ranges (0.55, 0.62, 0.69, 0.76, and 0.83 MPa) for condition monitoring of a reciprocating compressor

A talk about university - industry relationships, transfers and start-up creation

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