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

Current–time characteristics of resistive superconducting fault current limiters

Superconducting fault current limiters (SFCLs) may play an important role in power-dense electrical systems. Therefore, it is important to understand the dynamic characteristics of SFCLs. This will allow the behavior of multiple SFCLs in a system to be fully understood during faults and other transient conditions, which will consequently permit the coordination of the SFCL devices to ensure that only the device(s) closest to the fault location will operate. It will also allow SFCL behavior and impact to be taken into account when coordinating network protection systems. This paper demonstrates that resistive SFCLs have an inverse current-time characteristic: They will quench (become resistive) in a time that inversely depends upon the initial fault current magnitude. The timescales are shown to be much shorter than those typical of inverse overcurrent protection. A generic equation has been derived, which allows the quench time to be estimated for a given prospective fault current magnitude and initial superconductor temperature and for various superconducting device and material properties. This information will be of value to system designers in understanding the impact of SFCLs on network protection systems during faults and in planning the relative positions of multiple SFCLs

Application of multiple resistive superconducting fault-current limiters for fast fault detection in highly interconnected distribution systems

Superconducting fault-current limiters (SFCLs) offer several benefits for electrical distribution systems, especially with increasing distributed generation and the requirements for better network reliability and efficiency. This paper examines the use of multiple SFCLs in a protection scheme to locate faulted circuits, using an approach which is radically different from typical proposed applications of fault current limitation, and also which does not require communications. The technique, referred to as “current division discrimination” (CDD), is based upon the intrinsic inverse current-time characteristics of resistive SFCLs, which ensures that only the SFCLs closest to a fault operate. CDD is especially suited to meshed networks and particularly when the network topology may change over time. Meshed networks are expensive and complex to protect using conventional methods. Simulation results with multiple SFCLs, using a thermal-electric superconductor model, confirm that CDD operates as expected. Nevertheless, CDD has limitations, which are examined in this paper. The SFCLs must be appropriately rated for the maximum system fault level, although some variation in actual fault level can be tolerated. For correct coordination between SFCLs, each bus must have at least three circuits that can supply fault current, and the SFCLs should have identical current-time characteristics

Minerals For Sustainable Grain Yield And Grain Quality.

Rice cropping is an intensive enterprise. To be sustainable and to use water efficiently, rice requires adequate plant-essential nutrients. Nutrient supply has an impact on both grain yield and grain quality. In this project we have developed a nutrient balance model which summarises the impact of rice cropping on soil nutrients. The main concerns highlighted from this model are that, on average, all soil nutrients, except sulphur and calcium are being depleted. This work should alert rice growers to the potential for yield losses due to nutrient depletion. A plant nutrient diagnostic protocol is still required for Australian rice varieties. A protocol has been developed to induce the yield-reducing disorder known as straighthead. This will facilitate the design of studies aimed at understanding the cause of this problem. The current theory being tested is that micronutrient deficiencies, e.g., copper or zinc, cause the problem. Further testing is required to confirm the findings made up to now. This project has also demonstrated for the first time, that grain Fe and Zn can be increased in rice grains by as much as 44 and 26% respectively following applications of these elements in foliar fertilizers. During this study we also demonstrated the value of non-contaminating grain processing equipment for use in the study of micro-nutrients in rice. Variation in germplasm is seen as an asset to the breeding program. A literature review of world data from non-cultivated species of the genus Oryza has been assembled and will be a valuable source of information for plant breeders and other scientists seeking specific traits. During this study we also developed a new taxonomic key to aid the correct identification of the 4 Oryza species which are found in Australia. Rice accumulates phosphorus (P) to about 0.35% by weight in brown grains. As 85% of Australia’s rice is exported we sought germplasm to reduce this loss. Samples we obtained from a long-term study in Japan clearly demonstrated the impact of P-deficiency on grain yield and grain quality (low P, K and Mg concentrations). Preliminary studies were made at Yanco of the mutant rice known as lpa-1. The key feature of lpa-1 is that it deposits more phosphorus into inorganic P but less into organic or phytate P in the grain. We suggest that the line lpa-1 should be incorporated into high yielding Australian rices to produce a rice which could provide a better nutrient intake for humans and monogastric animals. Linkages have been established with the Yezin Agricultural University in Myanmar and the rice program of the Central Agricultural Research Institute. These linkages have the potential to boost our understanding of the nutrient requirements of rice under long-term cultivation and also provide access to cold-tolerant germplasm from regions with higher altitudes. This report represents the end of research supported by the Rice CRC . Project 2302 has enabled us to better understand the importance of nutrients to sustainable rice production but, at the same time, has left many promising lines of research worth further study

Analysis of energy dissipation in resistive superconducting fault-current limiters for optimal power system performance

Fault levels in electrical distribution systems are rising due to the increasing presence of distributed generation, and this rising trend is expected to continue in the future. Superconducting fault-current limiters (SFCLs) are a promising solution to this problem. This paper describes the factors that govern the selection of optimal SFCL resistance. The total energy dissipated in an SFCL during a fault is particularly important for estimating the recovery time of the SFCL; the recovery time affects the design, planning, and operation of electrical systems using SFCLs to manage fault levels. Generic equations for energy dissipation are established in terms of fault duration, SFCL resistance, source impedance, source voltage, and fault inception angles. Furthermore, using an analysis that is independent of superconductor material, it is shown that the minimum required volume of superconductors linearly varies with SFCL resistance but, for a given level of fault-current limitation and power rating, is independent of system voltage and superconductor resistivity. Hence, there is a compromise between a shorter recovery time, which is desirable, and the cost of the volume of superconducting material needed for the resistance required to achieve the shorter recovery time

An open platform for rapid-prototyping protection and control schemes with IEC 61850

Communications is becoming increasingly important to the operation of protection and control schemes. Although offering many benefits, using standards-based communications, particularly IEC 61850, in the course of the research and development of novel schemes can be complex. This paper describes an open-source platform which enables the rapid prototyping of communications-enhanced schemes. The platform automatically generates the data model and communications code required for an intelligent electronic device to implement a publisher-subscriber generic object-oriented substation event and sampled-value messaging. The generated code is tailored to a particular system configuration description (SCD) file, and is therefore extremely efficient at runtime. It is shown here how a model-centric tool, such as the open-source Eclipse Modeling Framework, can be used to manage the complexity of the IEC 61850 standard, by providing a framework for validating SCD files and by automating parts of the code generation process. The flexibility and convenience of the platform are demonstrated through a prototype of a real-time, fast-acting load-shedding scheme for a low-voltage microgrid network. The platform is the first open-source implementation of IEC 61850 which is suitable for real-time applications, such as protection, and is therefore readily available for research and education

AWAKE, The Advanced Proton Driven Plasma Wakefield Acceleration Experiment at CERN

The Advanced Proton Driven Plasma Wakefield Acceleration Experiment (AWAKE) aims at studying plasma wakefield generation and electron acceleration driven by proton bunches. It is a proof-of-principle R&D experiment at CERN and the world׳s first proton driven plasma wakefield acceleration experiment. The AWAKE experiment will be installed in the former CNGS facility and uses the 400 GeV/c proton beam bunches from the SPS. The first experiments will focus on the self-modulation instability of the long (rms ~12 cm) proton bunch in the plasma. These experiments are planned for the end of 2016. Later, in 2017/2018, low energy (~15 MeV) electrons will be externally injected into the sample wakefields and be accelerated beyond 1 GeV. The main goals of the experiment will be summarized. A summary of the AWAKE design and construction status will be presented