Self-tuning diagnosis of routine alarms in rotating plant items

Condition monitoring of rotating plant items in the energy generation industry is often achieved through examination of vibration signals. Engineers use this data to monitor the operation of turbine generators, gas circulators and other key plant assets. A common approach in such monitoring is to trigger an alarm when a vibration deviates from a predefined envelope of normal operation. This limit-based approach, however, generates a large volume of alarms not indicative of system damage or concern, such as operational transients that result in temporary increases in vibration. In the nuclear generation context, all alarms on rotating plant assets must be analysed and subjected to auditable review. The analysis of these alarms is often undertaken manually, on a case- by-case basis, but recent developments in monitoring research have brought forward the use of intelligent systems techniques to automate parts of this process. A knowledge- based system (KBS) has been developed to automatically analyse routine alarms, where the underlying cause can be attributed to observable operational changes. The initialisation and ongoing calibration of such systems, however, is a problem, as normal machine state is not uniform throughout asset life due to maintenance procedures and the wear of components. In addition, different machines will exhibit differing vibro- acoustic dynamics. This paper proposes a self-tuning knowledge-driven analysis system for routine alarm diagnosis across the key rotating plant items within the nuclear context common to the UK. Such a system has the ability to automatically infer the causes of routine alarms, and provide auditable reports to the engineering staff

Self-tuning routine alarm analysis of vibration signals in steam turbine generators

This paper presents a self-tuning framework for knowledge-based diagnosis of routine alarms in steam turbine generators. The techniques provide a novel basis for initialising and updating time series feature extraction parameters used in the automated decision support of vibration events due to operational transients. The data-driven nature of the algorithms allows for machine specific characteristics of individual turbines to be learned and reasoned about. The paper provides a case study illustrating the routine alarm paradigm and the applicability of systems using such techniques

Investigation of gas circulator response to load transients in nuclear power plant operation

Gas circulator units are a critical component of the Advanced Gas-cooled Reactor (AGR), one of the nuclear power plant (NPP) designs in current use within the UK. The condition monitoring of these assets is central to the safe and economic operation of the AGRs and is achieved through analysis of vibration data. Due to the dynamic nature of reactor operation, each plant item is subject to a variety of system transients of which engineers are required to identify and reason about with regards to asset health. The AGR design enables low power refueling (LPR) which results in a change in operational state for the gas circulators, with the vibration profile of each unit reacting accordingly. The changing conditions subject to these items during LPR and other such events may impact on the assets. From these assumptions, it is proposed that useful information on gas circulator condition can be determined from the analysis of vibration response to the LPR event. This paper presents an investigation into asset vibration during an LPR. A machine learning classification approach is used in order to define each transient instance and its behavioral features statistically. Classification and reasoning about the regular transients such as the LPR represents the primary stage in modeling higher complexity events for advanced event driven diagnostics, which may provide an enhancement to the current methodology, which uses alarm boundary limits

Machine learning model for event-based prognostics in gas circulator condition monitoring

Gas circulator (GC) units are an important rotating asset used in the Advanced Gas-cooled Reactor (AGR) design, facilitating the flow of CO2 gas through the reactor core. The ongoing maintenance and examination of these machines is important for operators in order to maintain safe and economic generation. GCs experience a dynamic duty cycle with periods of non-steady state behavior at regular refuelling intervals, posing a unique analysis problem for reliability engineers. In line with the increased data volumes and sophistication of available the technologies, the investigation of predictive and prognostic measurements has become a central interest in rotating asset condition monitoring. However, many of the state-of-the-art approaches finding success deal with the extrapolation of stationary time series feeds, with little to no consideration of more-complex but expected events in the data. In this paper we demonstrate a novel modelling approach for examining refuelling behaviors in GCs, with a focus on estimating their health state from vibration data. A machine learning model was constructed using the operational history of a unit experiencing an eventual inspection-based failure. This new approach to examining GC condition is shown to correspond well with explicit remaining useful life (RUL) measurements of the case study, improving on the existing rudimentary extrapolation methods often employed in rotating machinery health monitoring

Understanding the α-crystallin cell membrane conjunction

PURPOSE. It is well established that levels of soluble α-crystallin in the lens cytoplasm fall steadily with age, accompanied by a corresponding increase in the amount of membrane-bound α-crystallin. Less well understood, is the mechanism driving this age-dependent membrane association. The aim of this study was to investigate the role of the membrane and its associated proteins and peptides in the binding of α-crystallin. METHODS. Fibre cell membranes from human and bovine lenses were separated from soluble proteins by centrifugation. Membranes were stripped of associated proteins with successive aqueous, urea and alkaline solutions. Protein constituents of the respective membrane isolates were examined by SDS-PAGE and Western immunoblotting. Recombinant αA- and αB-crystallins were fluorescently-labeled with Alexa350® dye and incubated with the membrane isolates and the binding capacity of membrane for α-crystallin was determined. RESULTS. The binding capacity of human membranes was consistently higher than that of bovine membranes. Urea- and alkali-treated membranes from the nucleus had similar binding capacities for αA-crystallin, which were significantly higher than both cortical membrane extracts. αB-Crystallin also had a higher affinity for nuclear membrane. However, urea-treated nuclear membrane had three times the binding capacity for αB-crystallin as compared to the alkali-treated nuclear membrane. Modulation of the membrane-crystallin interaction was achieved by the inclusion of an N-terminal peptide of αB-crystallin in the assays, which significantly increased the binding. Remarkably, following extraction with alkali, full length αA- and αB-crystallins were found to remain associated with both bovine and human lens membranes. CONCLUSIONS. Fiber cell membrane isolated from the lens has an inherent capacity to bind α-crystallin. For αB-crystallin, this binding was found to be proportional to the level of extrinsic membrane proteins in cells isolated from the lens nucleus, indicating these proteins may play a role in the recruitment of αB-crystallin. No such relationship was evident for αA-crystallin in the nucleus, or for cortical membrane binding. Intrinsic lens peptides, which increase in abundance with age, may also function to modulate the interaction between soluble α-crystallin and the membrane. In addition, the tight association between α-crystallin and the lens membrane suggests that the protein may be an intrinsic component of the membrane structure

Electric Sail Tether Deployment System for CubeSats

An Electric Sail (E-Sail) propulsion system consists of long, thin tethers - positively-charged wires extending radially and symmetrically outward from a spacecraft. Tethers must be biased using a high-voltage power supply to ensure that the solar wind produces thrust. While the E-Sail concept shows great promise for flying heliopause missions with higher characteristic acceleration than solar sails, there are significant technical challenges related to deploying and controlling multiple tethers. A typical full-scale design involves a hub and spoke arrangement of 10 to 100 tethers, each 20 km long. In the last 20 years, there have been multiple space mission failures due to tether deployment and control issues, and most configurations involved a single tether. This paper describes an effort to develop and test a simple yet robust single-tether deployment system for a two-6U CubeSat configuration. The project included the following: a) Tether dynamic modeling/simulation b) E-Sail single-tether prototype development and testing c) Space environmental effects testing to identify best materials for further development. These three areas of investigation were needed to provide technical rationale for an E-Sail flight demonstration mission that is expected to be proposed for the 2022 time frame. The project team used an agile engineering approach in which E-Sail single-tether prototype designs were iteratively developed and tested to solve problems and identify design improvements. The agile approach was ideal for this low Technology Readiness Level (TRL) project because tether deployer development involved many unknowns in prototype development that could only be discovered through iterative cycles of construction and testing. Extensive modeling and simulation were accomplished for three types of tether deployment: a) Stage 1: propulsive separation with one 6U fixed b) Stage 2: propulsive spin-up with one 6U fixed c) Stage 3: propulsive spin-up with both 6Us free Simulation results were valuable for understanding the propulsive and braking forces needed for controlled tether deployment. This paper describes the evolution, insights, and test/ performance data related to the resultant single-tether two-6U E-Sail test article which has been demonstrated in a test laboratory. The development effort suggests near-term work needed to achieve a useful flight demonstration, and provides ideas for how multiple-tether deployment systems might evolve going forward. A planned next-generation E-Sail prototype will include autonomous propulsive tether deployment while monitoring tether tension, location on the floor, distance between tether ends, acceleration, velocity, and propellant used

Basic newborn resuscitation guidelines for healthcare providers in maragua district hospital: A best practice implementation project

Objective: The overall aim of this project was to assess compliance with evidence-based criteria regarding newborn resuscitation among healthcare workers in the maternity units in Maragua District Hospital (a busy district hospital in Kenya). Introduction: Globally, the majority of deaths under five years are attributable to neonatal causes. Perinatal asphyxia accounts for a significant portion of these deaths, especially in developing countries. These deaths are largely preventable, and interventions geared towards assisting newborns to initiate their first breath within the first minute of life have markedly reduced mortality. Methods: This implementation project was conducted in the maternity units of a busy district hospital. Evidencebased audit criteria were developed on the basis of an evidence summary developed by the Joanna Briggs Institute (JBI). Using the JBI Practical Application of Clinical Evidence System software (JBI PACES), a baseline audit was conducted including a sample size of 55 healthcare providers and 300 patient case notes followed by an identification of potential barriers and strategies to overcome them. A follow-up audit including a sample size of 55 healthcare providers was conducted by using the same audit criteria. Results: Improvements in practice were demonstrated in all criteria. The baseline audit demonstrated that three of the five audit criteriawere found to be less than 50%, indicatingmoderate compliancewith current evidencewith regards to newborn resuscitation. Following implementation of the strategies, which included a six-week education and demonstrative skills training, and updating of the protocols and equipment, there was a significant improvement in all the criteria audited, with the first four criteria achieving 100% compliance, and the fifth criteria achieving 90% compliance. Conclusion: On completion of the project, the participants demonstrated an increase in knowledge and skills on newborn resuscitation, which led to a significant reduction in admission of newborns with birth asphyxia to the newborn unit

Basic newborn resuscitation guidelines for healthcare providers in maragua district hospital: A best practice implementation project

Objective: The overall aim of this project was to assess compliance with evidence-based criteria regarding newborn resuscitation among healthcare workers in the maternity units in Maragua District Hospital (a busy district hospital in Kenya). Introduction: Globally, the majority of deaths under five years are attributable to neonatal causes. Perinatal asphyxia accounts for a significant portion of these deaths, especially in developing countries. These deaths are largely preventable, and interventions geared towards assisting newborns to initiate their first breath within the first minute of life have markedly reduced mortality. Methods: This implementation project was conducted in the maternity units of a busy district hospital. Evidencebased audit criteria were developed on the basis of an evidence summary developed by the Joanna Briggs Institute (JBI). Using the JBI Practical Application of Clinical Evidence System software (JBI PACES), a baseline audit was conducted including a sample size of 55 healthcare providers and 300 patient case notes followed by an identification of potential barriers and strategies to overcome them. A follow-up audit including a sample size of 55 healthcare providers was conducted by using the same audit criteria. Results: Improvements in practice were demonstrated in all criteria. The baseline audit demonstrated that three of the five audit criteriawere found to be less than 50%, indicatingmoderate compliancewith current evidencewith regards to newborn resuscitation. Following implementation of the strategies, which included a six-week education and demonstrative skills training, and updating of the protocols and equipment, there was a significant improvement in all the criteria audited, with the first four criteria achieving 100% compliance, and the fifth criteria achieving 90% compliance. Conclusion: On completion of the project, the participants demonstrated an increase in knowledge and skills on newborn resuscitation, which led to a significant reduction in admission of newborns with birth asphyxia to the newborn unit

Trigger for group A streptococcal M1T1 invasive disease

The globally disseminated Streptococcus pyogenes M1T1 clone causes a number of highly invasive human diseases. The transition from local to systemic infection occurs by an unknown mechanism; however invasive M1T1 clinical isolates are known to express significantly less cysteine protease SpeB than M1T1 isolates from local infections. Here, we show that in comparison to the M1T1 strain 5448, the isogenic mutant ΔspeB accumulated 75‐fold more human plasmin activity on the bacterial surface following incubation in human plasma. Human plasminogen was an absolute requirement for M1T1 strain 5448 virulence following subcutaneous (s.c.) infection of humanized plasminogen transgenic mice. S. pyogenes M1T1 isolates from the blood of infected humanized plasminogen transgenic mice expressed reduced levels of SpeB in comparison with the parental 5448 used as inoculum. We propose that the human plasminogen system plays a critical role in group A streptococcal M1T1 systemic disease initiation. SpeB is required for S. pyogenes M1T1 survival at the site of local infection, however, SpeB also disrupts the interaction of S. pyogenes M1T1 with the human plasminogen activation system. Loss of SpeB activity in a subpopulation of S. pyogenes M1T1 at the site of infection results in accumulation of surface plasmin activity thus triggering systemic spread.—Cole, J. N., McArthur, J. D., McKay, F. C., Sanderson‐Smith, M. L., Cork, A. J., Ranson, M., Rohde, M., Itzek, A., Sun, H., Ginsburg, D., Kotb, M., Nizet, V., Chhatwal, G. S., Walker, M. J. Trigger for group A streptococcal M1T1 invasive disease. FASEB J. 20, E1139–E1145 (2006)Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154248/1/fsb2fj065804fje.pd