Advanced Fault Diagnosis and Health Monitoring Techniques for Complex Engineering Systems

Over the last few decades, the field of fault diagnostics and structural health management has been experiencing rapid developments. The reliability, availability, and safety of engineering systems can be significantly improved by implementing multifaceted strategies of in situ diagnostics and prognostics. With the development of intelligence algorithms, smart sensors, and advanced data collection and modeling techniques, this challenging research area has been receiving ever-increasing attention in both fundamental research and engineering applications. This has been strongly supported by the extensive applications ranging from aerospace, automotive, transport, manufacturing, and processing industries to defense and infrastructure industries

Friction, Vibration and Dynamic Properties of Transmission System under Wear Progression

This reprint focuses on wear and fatigue analysis, the dynamic properties of coating surfaces in transmission systems, and non-destructive condition monitoring for the health management of transmission systems. Transmission systems play a vital role in various types of industrial structure, including wind turbines, vehicles, mining and material-handling equipment, offshore vessels, and aircrafts. Surface wear is an inevitable phenomenon during the service life of transmission systems (such as on gearboxes, bearings, and shafts), and wear propagation can reduce the durability of the contact coating surface. As a result, the performance of the transmission system can degrade significantly, which can cause sudden shutdown of the whole system and lead to unexpected economic loss and accidents. Therefore, to ensure adequate health management of the transmission system, it is necessary to investigate the friction, vibration, and dynamic properties of its contact coating surface and monitor its operating conditions

THE INVESTIGATION INTO THE CONDITION MONITORING OF TRIBOLOGICAL BEHAVIOUR BETWEEN PISTON RING AND CYLINDER LINER USING ACOUSTIC EMISSIONS

To improve engine operational performance and reliability, this study focuses on the investigation into the behaviour of tribological conjunction between the ring - liner based on a comprehensive analysis of non-intrusive acoustic emission (AE) measurement. Particularly, the study will provide more knowledge of using AE for online monitoring and diagnosing the performances of the conjunction. To fulfil this study, it integrates analytical predictions of the theoretical modelling for the AE generation mechanism with extensive experimental evaluations. Moreover, effective signal processing techniques are implemented with a combination of the model based AE predictions to extract the weak and nonstationary AE contents that correlate more with the tribological behaviour. Based on conventional tribological models, tribological AE is modelled to be due to two main dynamic effects: asperity-asperity collision (AAC) and fluid-asperity interaction (FAI), which allows measured AE signals from the tribological conjunction to be explained under different scenarios, especially under abnormal behaviours. FAI induced AE is more correlated with lubricants and velocity. It presents mainly in the middle of engine strokes but is much weaker and severely interfered with AEs from not only valve landings, combustion and fuel injection shocks but also the effect of considerable AACs due to direct contacts and solid particles in oils. To extract weak AEs for accurately diagnosing the tribological behaviours, wavelet transform analysis is applied to AE signals with three novel schemes: 1) hard threshold based wavelet coefficients selection in which the threshold value and wavelet analysis parameters are determined using a modified velocity of piston motion which has high dependence on the AE characteristics predicted by the two models; 2) Adaptive threshold wavelet coefficients selection in which the threshold is gradually updated to minimise the distance between the AE envelopes and the predicted dependence; and 3) wavelet packet transform (WPT) analysis is carried out by an optimised Daubechies wavelet through a novel approach based on minimising the time and frequency overlaps in WPT spectrum. Based on these optimal analyses, the local envelope amplitude (LEA) and the average residual wavelet coefficient (ARWC) are developed from AE signals as novel indicators to reflect the tribological behaviours.\ud Both the hard threshold based LEA and wavelet packet transform LEA values allow two different new lubricants to be diagnosed in accordance with model predictions whereas they produce less consistent results in differentiating the used oil under several operating conditions. Nevertheless, ARWC can separate the used oil successfully in that it can highlight the AAC effects of particle collisions in used oils. Similarly, LEA shows little impacts of two alternative fuels on the tribological behaviours. However, ARWC shows significantly higher amplitudes in several operating conditions when more particles can be produced due to unstable and incomplete combustions of both the biodiesel and FT diesel, compared with pure diesel, indicating they can cause light wear

30th International Conference on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2017)

Proceedings of COMADEM 201

Characterising Vibro-Acoustic Signals of a Reciprocating Compressor for Condition Monitoring

Machine monitoring in industries such as chemical process plants, petroleum refineries and pulp and paper industries has significantly increased over the years, mainly because of the economic impact associated with the breakdown of a piece of equipment. With downtime sometimes costing up to 100,000 USD a day (Wachel, N.D), industrial organisations have made it mandatory to put in place systems for monitoring the condition of critical machines used for production purposes to prevent unforeseen machine breakdown. Reciprocating compressors are one of the widely used compressor types in diverse fields of application particularly in the oil and gas industry or chemical industry. In these industries, reciprocating compressors are mainly used to deliver high-pressure gas from one location to another. Due to the importance of these machines in delivering high-pressured air and sometimes toxic gases safely, their reliability has gained widespread interest over the years. To improve reciprocating compressor operational performance and reliability, this research focuses on investigating the characteristics of vibro-acoustic signals from a reciprocating compressor based on a comprehensive analysis of non-intrusive vibration measurement and discharge gas oscillations (pulsations). This study will provide more knowledge on using two techniques (vibration and gas pulsations) for online monitoring and diagnosing of reciprocating compressor faults. Other monitoring techniques such as in-cylinder pressure, instantaneous angular speed (IAS), airborne acoustic as well as vibration are previously reported in literature, however, it is believed that no information for condition monitoring of discharge gas pulsation of a reciprocating compressor has been explored. To fulfil this study, in-depth modelling and an extensive experimental evaluation for different and combined faults common to reciprocating compressor systems are explored for a wide discharge pressure range to better understand the vibro-acoustic sources. Three common faults including discharge valve leakage, intercooler leakage, discharge pipeline leakage and two combined faults: discharge valve leakage and intercooler leakage, discharge valve leakage and discharge pipeline leakage under various discharge pressures are studied in this thesis. The simulation of compressor performance with and without faults for several discharge pressures were in good agreements with the corresponding experimental evaluations, and was used to understand the compressor dynamics. Furthermore, a preliminary study on the effectiveness of conventional methods such as time-domain and frequency-domain analysis of both vibration and gas pulsation measurements were investigated. Results show that, these traditional methods were insufficient in revealing fault characteristics in the vibration signal due to the usual noise contamination and nonstationary nature of the signal. Although, with the gas pulsation signal, waveform patterns and resonant frequencies varied with faults at several discharge pressures, nevertheless, effective band pass filtering needed to identify the best frequency band that can represent the characteristic behaviour of gas pulsation signals proofed difficult and time consuming. Amongst several advanced signal-processing approaches reviewed such as wavelet transform, time synchronous average, Hilbert transform, and empirical mode decomposition; wavelet packet transform is regarded as the most powerful tool to describe gas pulsation and vibration fault signals in different frequency bands. A combination of wavelet packet transform (WPT) and Hilbert transform (envelope analysis) is proposed to achieve optimal and effective band pass filtering for resonance band identification in gas pulsation signals, and WPTs de-noising property, which can effectively reduce excessive noise revealing key transient features in vibration signals. Optimal band selection for vibration signal was achieved using entropy computation. The band with the highest entropy was used to reconstruct the signal and the envelope of the new vibration signal was used for classification. The fundamental frequency and its harmonics were used as a tool for fault classification. All fault conditions were clearly separated using the fundamental frequency and its third (3X) harmonic. Regarding gas pulsation signals, the optimal band was selected by computing the root mean square (RMS) values of all eight enveloped band signals for several discharge pressures and faults. The band with the best RMS separation trend was selected for further classification using two main diagnostic features: the kurtosis and entropy of optimal band. The plot of kurtosis against entropy as a diagnostic tool showed good valve fault classification across a wide discharge pressure range. Although the analysis of vibration signal using the proposed methods gave more reliable results for reciprocating compressor fault detection and diagnosis compared to the gas pulsation results, analysis of gas pulsation signals gave a better result on the optimal frequency band selection that can represent the behaviour of reciprocating compressor (RC) valve fault. Therefore, it can be deduced that analysis of the RC vibration signal together with the gas pulsation signal has a promising potential to be used for condition monitoring and fault diagnostics of reciprocating compressors online

Compound Fault Diagnosis of Centrifugal Pumps Using Vibration Analysis Techniques

Centrifugal pumps are widely used in many different industrial processes, such as power generation stations, chemical processing plants, and petroleum industries. The problem of failures in centrifugal pumps is a large concern due to its significant influence on such critical industries. Particularly, as the core, parts of a pump, bearings and the impellers are subject to different corrosions and their faults can cause major degradation of pump performances and lead to the breakdown of production. Therefore, an early detection of these types of faults would provide information to take timely preventive actions. This research investigates more effective techniques for diagnosing common faults of impellers and bearings with advanced signal analysis of surface vibration. As overall vibration responses contain a high level of broadband noises due to fluid cavities and turbulences, noise reduction is critical to developing reliable and accurate features. However, considering the modulation effect between the rotating shaft, vane passing components and any structural resonances, a modulation signal bispectrum (MSB) method is mainly used to extract these deterministic characteristics of modulations, which differs from previous researches in that the broadband vibration is often characterised with statistical methods, high frequency demodulation along spectrum analysis. Both theoretical analysis and experimental evaluation show that the diagnostic features developed by MSB allow impellers with inlet vane damages and exit vane faults to be identified under different operating conditions. It starts with an in-depth examination of the vibration excitation mechanisms associated with each type of common pump faults including impeller leakages, impeller blockages, bearing inner race defects and bearing outrace defects. Subsequently, fault diagnosis was carried out using popular spectrum and envelope analysis, and more advanced kurtogram and MSB analysis. These methods all can successfully provide correct detection and diagnosis of the faults, which are induced manually to the test pump. Envelope analysis in a bands optimised with Kurtogram produces outstanding detection results for bearing faults but not the impeller faults in a frequency range as high as several thousand hertz (about 7.5kHz). In addition, it cannot provide satisfactory diagnostic results in separating the faults across different flow rates, especially when the compound faults were evaluated. This deficiency is because they do not have the capability of suppressing the random noises. Meanwhile, it has found that the MSB analysis allows both impeller and bearing faults to be detected and diagnosed. Especially, when the pump operated with compound faults both the fault types and severity can be attained by the analysis with acceptable accuracy for different flow rates. This high performance of diagnosis is due to that MSB has the unique capability of noise reduction and nonlinearity demodulation. Moreover, MSB diagnosis can be a frequency range lower than 2 times of the blade pass frequency (<1kHz), meaning that it can be more cost-effective as it demands lower performance measurement systems. In addition, the study also found that one accelerometer mounted on the pump housing is sufficient to monitor the faults on both the impeller and the bearing as it uses a lower frequency vibration which propagates far away from the bearing to the housing, rather than another accelerometer on the bearing pedestal directly