Diesel engine fuel injection monitoring using acoustic measurements and independent component analysis

Air-borne acoustic based condition monitoring is a promising technique because of its intrusive nature and the rich information contained within the acoustic signals including all sources. However, the back ground noise contamination, interferences and the number of Internal Combustion Engine ICE vibro-acoustic sources preclude the extraction of condition information using this technique. Therefore, lower energy events; such as fuel injection, are buried within higher energy events and/or corrupted by background noise. This work firstly investigates diesel engine air-borne acoustic signals characteristics and the benefits of joint time-frequency domain analysis. Secondly, the air-borne acoustic signals in the vicinity of injector head were recorded using three microphones around the fuel injector (120° apart from each other) and an Independent Component Analysis (ICA) based scheme was developed to decompose these acoustic signals. The fuel injection process characteristics were thus revealed in the time-frequency domain using Wigner-Ville distribution (WVD) technique. Consequently the energy levels around the injection process period between 11 and 5 degrees before the top dead center and of frequency band 9 to 15 kHz are calculated. The developed technique was validated by simulated signals and empirical measurements at different injection pressure levels from 250 to 210 bars in steps of 10 bars. The recovered energy levels in the tested conditions were found to be affected by the injector pressure settings

Modeling and Control for Smart Grid Integration of Solar/Wind Energy Conversion System

Performance optimization, system reliability and operational efficiency are key characteristics of smart grid systems. In this paper a novel model of smart grid-connected PV/WT hybrid system is developed. It comprises photovoltaic array, wind turbine, asynchronous (induction) generator, controller and converters. The model is implemented using MATLAB/SIMULINK software package. Perturb and observe (P&O) algorithm is used for maximizing the generated power based on maximum power point tracker (MPPT) implementation. The dynamic behavior of the proposed model is examined under different operating conditions. Solar irradiance, temperature and wind speed data is gathered from a grid connected, 28.8kW solar power system located in central Manchester. Real-time measured parameters are used as inputs for the developed system. The proposed model and its control strategy offer a proper tool for smart grid performance optimization

A new approach to the cohesive zone model that includes thermal effects

© 2019 This study presents a cohesive zone model combining mechanical and thermal effects. Thermal stress was added to the Helmholtz free energy density in order to derive a new approach to incremental damage which included the effect of temperature. The developed damage model has been implemented in ABAQUS using the UMAT subroutine and applied of two different specimens; a three-point bending specimen and a Double Cantilever Beam. The effectiveness of the new method was tested for the given specimens at different temperatures. The simulation results revealed that the total energy of the interface element of high strength carbon fiber reinforced plastic increased as its temperature decreased. It is demonstrated that the load-displacement curves obtained from the numerical model for both test specimens were in good agreement with experimental data available in literature

Regulation of cell fate by lymphotoxin (LT) receptor signalling: Functional differences and similarities of the LT system to other TNF superfamily (TNFSF) members

The role of TNFR family members in regulating cell fate both in the immune system and in non-lymphoid tissues has been under extensive research for decades. Moreover, the ability of several family members (death receptors) to induce death (mainly via apoptosis) represents a promising target for cancer therapy. Many studies have focused mostly on death receptors such as TNFRI, Fas and TRAIL-R due to their strong pro-apoptotic potential. Yet, cell death can be triggered via non-classical death receptors, and the Lymphotoxin (LT) system represents a very good example of such a TNFR subfamily. Here we provide a comprehensive review of intracellular signalling pathways and cellular responses to LTspecific signalling, and compare for the first time the LT system to other TNFRs, such as CD40. Our aim is to highlight that non-classical TNFR-TNFL dyads such as the LT system demonstrate more complex, cell-type and context-specific capabilities. Understanding these complexities will permit a better understanding of the biological mechanisms via which nondeath domain-containing TNFRs induce cell death, but may also allow the design of better therapeutic strategies

Reliability Assessment of IGBT through Modelling and Experimental Testing

Lifetime of power electronic devices, in particular those used for wind turbines, is short due to the generation of thermal stresses in their switching device e.g., IGBT particularly in the case of high switching frequency. This causes premature failure of the device leading to an unreliable performance in operation. Hence, appropriate thermal assessment and implementation of associated mitigation procedure are required to put in place in order to improve the reliability of the switching device. This paper presents two case studies to demonstrate the reliability assessment of IGBT. First, a new driving strategy for operating IGBT based power inverter module is proposed to mitigate wire-bond thermal stresses. The thermal stress is characterised using finite element modelling and validated by inverter operated under different wind speeds. High-speed thermal imaging camera and dSPACE system are used for real time measurements. Reliability of switching devices is determined based on thermoelectric (electrical and/or mechanical) stresses during operations and lifetime estimation. Second, machine learning based data-driven prognostic models are developed for predicting degradation behaviour of IGBT and determining remaining useful life using degradation raw data collected from accelerated aging tests under thermal overstress condition. The durations of various phases with increasing collector-emitter voltage are determined over the device lifetime. A data set of phase durations from several IGBTs is trained to develop Neural Network (NN) and Adaptive Neuro Fuzzy Inference System (ANFIS) models, which is used to predict remaining useful life (RUL) of IGBT. Results obtained from the presented case studies would pave the path for improving the reliability of IGBTs

The role of lymphotoxin ligand-receptor interactions in regulating epithelial cell fate

LTβR and HVEM are non-death domain-containing TNFRs that can induce cell death via possible recruitment of TNFR-associated factors (TRAF), thus may share similarities to other TNFR members (e.g. CD40). This thesis aimed to investigate the effects of soluble LT agonists on a panel of carcinoma cells of colorectal (CRC) and bladder (UCC) origins and to compare the ability of these agonists to induce cell death against membrane-bound LIGHT (mLIGHT), and to unravel for the first time the cell signalling pathways responsible for mLIGHT-mediated cell death. Due to the complexity of some of the approaches used, a significant part of the experimental work involved optimisations involving not only soluble LT agonists, cytokines, specific pharmacological inhibitors but mainly optimisation for the first time of a co-culture system for the delivery of the mLIGHT signal to epithelial cells (involved co-culture of target cells with growth-arrested third-party L cells expressing surface mLIGHT). Several assays were also optimised for detection of cell viability, cell death (based on protease release, caspase activation and DNA fragmentation) and for detection of pro-inflammatory cytokine secretion. Moreover, immunoblotting techniques were optimised and utilised for detection of proteins associated with intracellular LTβR and HVEM-signalling. Transfection experiments using specific small interfering RNAs (siRNAs) were also employed to knockdown the expression of LTβR and HVEM proteins in CRC and UCC cells. This project revealed for the first time that normal human urothelial cells (NHU), CRC and UCC cells express LTβR and HVEM, and that the activation of LTβR and HVEM by mLIGHT, in the absence of IFN-γ, is pro-apoptotic in carcinoma cells, whereas mLIGHT appeared to be cyto-protective in NHU cells. By contrast, soluble LT agonists were weakly pro-apoptotic and required IFN-γ to kill HT29 cells, yet this combination did not kill other, well-characterised carcinoma cell lines, in particular HCT116 and EJ cells. Moreover, mLIGHT caused some DNA fragmentation in HCT116, yet little DNA fragmentation was detected in HT29 and EJ cells. It was also found that mLIGHT caused IL-8 and GM-CSF secretion. mLIGHT triggered TRAF1 and TRAF3 induction and caused little detectable differences in phospho-ERK, -JNK and -p38 expression in CRC and UCC cells. Functional inhibition experiments showed that blockade of MEK/ERK abrogated death in all cell lines tested, and JNK inhibition attenuated death in HCT116 and EJ (but not HT29 cells) and p38 inhibition significantly attenuated, but not fully, mLIGHT-mediated cell death in CRC and UCC cells. Moreover, an NF-κB inhibitor partially reduced mLIGHT-mediated death in CRC cells and potentiated it in UCC cells, whereas, inhibition of AP-1 partially blocked mLIGHT-mediated death in HCT116 and EJ cells. By contrast, AP-1 blockade did not cause any statistically significant effect in mLIGHT-mediated death in HT29 cells. Moreover, mLIGHT-mediated death is ROS dependent in CRC and UCC cells as the antioxidant NAC attenuated death. The current work has also provided evidence for the first time that a role for NOX enzyme in cell death of HCT116 and EJ cells as it was found that mLIGHT induced the phosphorylation of p40phox (a subunit of NOX). Importantly, despite observing that ASK1 was activated in HCT116 cells, but not other cells, mLIGHT caused downregulation of Thioredoxin-1 expression in CRC and UCC. siRNA experiments for LTβR and HVEM knockdown showed some preliminary evidence that LTβR and HVEM might signal cooperatively in the context of LIGHT-mediated cell death. Collectively, this thesis has demonstrated for the first time that triggering cell death in CRC and UCC is clearly dependent on signal quality, cell-type specificity and death is tumour cell-specific. The current study has also provided some mechanistic insight into how cell death induced by mLIGHT-LTβR/HVEM interactions occurs, which may involve a novel pathway of receptor-TRAF3-MAPK-NOX interactions, which utilise ROS for the activation of cell death pathways in CRC and UCC cells. These findings have not only improved our understanding of how TNFRs induce carcinoma cells death, but may also help in the design of better therapeutic strategies in the future

Frequency Adaptive Parameter Estimation of Unbalanced and Distorted Power Grid

Grid synchronization plays an important role in the grid integration of renewable energy sources. To achieve grid synchronization, accurate information of the grid voltage signal parameters are needed. Motivated by this important practical application, this paper proposes a state observer-based approach for the parameter estimation of unbalanced three-phase grid voltage signal. The proposed technique can extract the frequency of the distorted grid voltage signal and is able to quantify the grid unbalances. First, a dynamical model of the grid voltage signal is developed considering the disturbances. In the model, frequency of the grid is considered as a constant and/or slowly-varying but unknown quantity. Based on the developed dynamical model, a state observer is proposed. Then using Lyapunov function-based approach, a frequency adaptation law is proposed. The chosen frequency adaptation law guarantees the global convergence of the estimation error dynamics and as a consequence, ensures the global asymptotic convergence of the estimated parameters in the fundamental frequency case. Gain tuning of the proposed state observer is very simple and can be done using Matlab commands. Some guidelines are also provided in this regard. Matlab/Simulink based numerical simulation results and dSPACE 1104 board-based experimental results are provided. Test results demonstrate the superiority and effectiveness of the proposed approach over another state-of-the art technique

Adoption of MEMS technology in e-maintenance systems for rotating machinery

Microelectromechanical systems (MEMS)-based sensing networks with on-board signal processing capabilities are becoming very attractive for monitoring the condition of rotating and static equipment. Their advantages in cost and size are an important factor for deployment in a new generation of maintenance called e-maintenance. In this paper, an intelligent monitoring system for e-maintenance (IMSEM) was developed using MEMS accelerometers, a low-power microprocessor and a wireless communication module. The system has a compatible framework and interface with open system architecture for condition-based maintenance (OSA-CBM). It integrates OSA-CBM-defined functions, including a sensing module, signal processing, condition monitoring and health assessment. Thus, the developed system successfully reduced the monitoring complexity and communication overhead with human operators. The performance of IMSEM is evaluated by carrying out fault diagnostics on the rotating unbalance of a mechanical shaft driven by a direct current (DC) motor with varying load and speed. Five statistical features were calculated for 63 vibration datasets. 25 datasets were used to train a support vector machine, with a linear kernel, and the other 38 sets were used for binary classification. About 94.7% of unknown conditions were successfully classified as healthy/unhealthy based on all features, which was improved to 100% using the best three features. This has demonstrated the capability of the developed system in detecting faults and the severity of rotor unbalance, based on ISO 1940-1:2003

Effective Technique for Improving Electrical Performance and Reliability of Fuel Cells

To optimise the electrical performance of proton exchange membrane (PEM) fuel cells, a number of factors have to be precisely monitored and controlled. Water content is one of those factors that has great impact on reliability, durability and performance of PEM fuel cells. The difficulty in controlling water content lies in the inability to determine correct level of water accumulated inside the fuel cell. In this paper, a model-based technique, implemented in COMSOL, is presented for monitoring water content in PEM fuel cells. The model predicts, in real time, water content taking account of other processes occurring in gas channels, across gas diffusion layers (GDL), electrodes, and catalyst layer (CL) and within the membrane to minimize voltage losses and performance degradation. The level of water generated is calculated as function of cell’s voltage and current. Model’s performance and accuracy are verified using a transparent 500 mW PEM fuel cell. Results show model predicted current and voltage curves are in good agreement with the experimental measurements. The unique feature of this model is that, no special requirements are needed as only current, and voltage of the PEM fuel cell were measured thus, is expected to pave the path for developing non-intrusive control and monitoring systems for fuel cells

The sensitivity of 5MW wind turbine blade sections to the existence of damage

Due to the large size of offshore wind turbine blades (OWTBs) and the corrosive nature of salt water, OWTs need to be safer and more reliable that their onshore counterparts. To ensure blade reliability, an accurate and computationally efficient structural dynamic model is an essential ingredient. If damage occurs to the structure, the intrinsic properties will change, e.g., stiffness reduction. Therefore, the blade’s dynamic characteristics will differ from those of the intact ones. Hence, symptoms of the damage are reflected in the dynamic characteristics that can be extracted from the damaged blade. Thus, damage identification in OWTBs has become a significant research focus. In this study, modal model characteristics were used for developing an effective damage detection method for WTBs. The technique was used to identify the performance of the blade’s sections and discover the warning signs of damage. The method was based on a vibration-based technique. It was adopted by investigating the influence of reduced blade element rigidity and its effect on the other blade elements. A computational structural dynamics model using Rayleigh beam theory was employed to investigate the behaviour of each blade section. The National Renewable Energy Laboratory (NREL) 5MW blade benchmark was used to demonstrate the behaviour of different blade elements. Compared to previous studies in the literature, where only the simple structures were used, the present study offers a more comprehensive method to identify damage and determine the performance of complicated WTB sections. This technique can be implemented to identify the damage’s existence, and for diagnosis and decision support. The element most sensitive to damage was element number 14, which is NACA_64_618