Practical applications of data mining in plant monitoring and diagnostics

Using available expert knowledge in conjunction with a structured process of data mining, characteristics observed in captured condition monitoring data, representing characteristics of plant operation may be understood, explained and quantified. Knowledge and understanding of satisfactory and unsatisfactory plant condition can be gained and made explicit from the analysis of data observations and subsequently used to form the basis of condition assessment and diagnostic rules/models implemented in decision support systems supporting plant maintenance. This paper proposes a data mining method for the analysis of condition monitoring data, and demonstrates this method in its discovery of useful knowledge from trip coil data captured from a population of in-service distribution circuit breakers and empirical UHF data captured from laboratory experiments simulating partial discharge defects typically found in HV transformers. This discovered knowledge then forms the basis of two separate decision support systems for the condition assessment/defect clasification of these respective plant items

Collaboration for diagnosis of Xanthomonas citri pv. mangiferaeindicae causing mango bacterial canker on Mangifera indica in Myanmar : [P2-10]

During 2006-2008, mango disease survey training for pest Iist development was supported under the ASEAN Australia Development Co-operation Program (AADCP) Program Stream: Strengthening ASEAN Plant Health Capacity Project (1). The project involved regional training workshops and practical experience in surveying and disease diagnostics in selected ASEAN countries, in partnership with Australian mango pest and disease specialists. The surveying also provided an opportunity for extending collaboration with CIRAD and for strengthening CIRAD-ASEAN links, when specialist expertise in bacterial disease diagnostics was required. Bacterial canker of mango (or bacterial black spot) caused by #Xanthomonas citri pv. Mangiferaeindicae# (2) is a disease of economic importance in tropical and subtropical producing areas. #X. citri pv. Mangiferaeindicae# can cause severe infection in a wide range of mango cultivars and induces raised, angular, black leaf lesions, sometimes with a chlorotic halo. Suspected leaf lesions of bacterial canker were collected from mango nursery stock cv. Yin Kwe at a nursery in Yangon, Myanmar during March 2007. Sub-samples of representative accessions were dispatched by air-courier to 2CIRAD UMR PVBMT, La Réunion, with additional reference material retained in the plant disease herbarium of'PPD. In tests at CIRAD UMR PVBMT2, nonpigmented Xanthomonas-like bacterial colonies were isolated on KC and NCTM3 semiselective agar media (4,7). Amplified fragment length polymorphism analysis was performed on three isolates from Myanmar and additional reference isolates of xanthomonads originating from Anacardiaceae (#X. citri pv. Anacardii#, #X. citri pv. Mangiferaeindicae#, #X. axonopodis pv. Spondiae#, and #X. translucens# strains from pistachio) (2, 4). On the basis of multidimensional scaling (2), the Myanmar isolates were identified as #X. citri pv. Mangiferaeindicae# and were most closely related to group B strains that were isolated from mango in India and Eastern Asia (5). Mango cv. Maison Rouge leaves, inoculated as previously reported (3) with the Myanmar isolates, showed typical symptoms of bacterial canker 1 week after inoculation. One month after inoculation, mean #X. citri pv. Mangiferaeindicae# population sizes ranging from 5 x 106 to 8 x 106 CFU per lesion were recovered from leaf lesions, typical of a compatible interaction (3). #Mangifera indica# L. probably evolved in the area that includes northwestern Myanmar (6) and to our knowledge, this is the first confirmed detection of #X. citri pv. Mangiferaeindicae# from Myanmar. Further surveys and strain collection will be necessary to evaluate its geographic distribution and prevalence in the country (4). The diagnosis and confirmation of bacterial spot on mango from Myanmar (4) has assisted in the development of Myanmar's mango pest list, and enabled Myanmar partners to gain experience in international collaboration in plant disease specimen dispatch and diagnostics. (Résumé d'auteur

Diagnostic systems in DEMO: engineering design issues

The diagnostic systems of DEMO that are mounted on or near the torus, whether intended for the monitoring and control functions of the engineering aspects or the physics behaviour of the machine, will have to be designed to suit the hostile nuclear environment. This will be necessary not just for their survival and correct functioning but also to satisfy the pertinent regulatory bodies, especially where any of them relate to machine protection or the prevention or mitigation of accidents foreseen in the safety case. This paper aims to indicate the more important of the reactor design considerations that are likely to apply to diagnostics for DEMO, drawn from experience on JET, the provisions in hand for ITER and modelling results for the wall erosion and neutron damage effects in DEMO.Comment: 8 page

System-level key performance indicators for building performance evaluation

Quantifying building energy performance through the development and use of key performance indicators (KPIs) is an essential step in achieving energy saving goals in both new and existing buildings. Current methods used to evaluate improvements, however, are not well represented at the system-level (e.g., lighting, plug-loads, HVAC, service water heating). Instead, they are typically only either measured at the whole building level (e.g., energy use intensity) or at the equipment level (e.g., chiller efficiency coefficient of performance (COP)) with limited insights for benchmarking and diagnosing deviations in performance of aggregated equipment that delivers a specific service to a building (e.g., space heating, lighting). The increasing installation of sensors and meters in buildings makes the evaluation of building performance at the system level more feasible through improved data collection. Leveraging this opportunity, this study introduces a set of system-level KPIs, which cover four major end-use systems in buildings: lighting, MELs (Miscellaneous Electric Loads, aka plug loads), HVAC (heating, ventilation, and air-conditioning), and SWH (service water heating), and their eleven subsystems. The system KPIs are formulated in a new context to represent various types of performance, including energy use, peak demand, load shape, occupant thermal comfort and visual comfort, ventilation, and water use. This paper also presents a database of system KPIs using the EnergyPlus simulation results of 16 USDOE prototype commercial building models across four vintages and five climate zones. These system KPIs, although originally developed for office buildings, can be applied to other building types with some adjustment or extension. Potential applications of system KPIs for system performance benchmarking and diagnostics, code compliance, and measurement and verification are discussed

Variable number of tandem repeat markers in the genome sequence of Mycosphaerella fijiensis, the causal agent of black leaf streak disease of banana (Musa spp)

ABSTRACT. We searched the genome of Mycosphaerella fijiensis for molecular markers that would allow population genetics analysis of this plant pathogen. M. fijiensis, the causal agent of banana leaf streak disease, also known as black Sigatoka, is the most devastating pathogen attacking bananas (Musa spp). Recently, the entire genome sequence of M. fijiensis became available. We screened this database for VNTR markers. Forty-two primer pairs were selected for validation, based on repeat type and length and the number of repeat units. Five VNTR markers showing multiple alleles were validated with a reference set of isolates from different parts of the world and a population from a banana plantation in Costa Rica. Polymorphism information content values varied from 0.6414 to 0.7544 for the reference set and from 0.0400 and 0.7373 for the population set. Eighty percent of the polymorphism information content values were above 0.60, indicating that the markers are highly informative. These markers allowed robust scoring of agarose gels and proved to be useful for variability and population genetics studies. In conclusion, the strategy we developed to identify and validate VNTR markers is an efficient means to incorporate markers that can be used for fungicide resistance management and to develop breeding strategies to control banana black leaf streak disease. This is the first report of VNTR-minisatellites from the M. fijiensis genome sequence. Key words: Molecular markers; VNTRs; Genetic diversity; Population genetics; Black Sigatok

Visacane, an innovative quarantine tool for the exchange of pest and disease-free sugarcane germplasm

Sugarcane varietal improvement can not exclusively rely upon exchange and introduction of genetic resources via true seeds (fuzz). It also requires the introduction of vegetative propagation material (cuttings, tissue-cultured plantlets). The continued increase in international and intercontinental trade in plants has led to the enforcement of quarantine measures before introduction into a country because many plant pathogens can be carried and transmitted by vegetatively propagated material. Visacane is the new name of Cirad's sugarcane quarantine (http://visacane.cirad.fr/en/). It covers three main quarantine procedures: detection of pests and pathogens, elimination of pests and pathogens, and transfer of plant material free of pests and pathogens. It has been devoted to sugarcane quarantining for several decades. Besides phytosanitary constraints, Visacane takes also into account legal constraints and ensures, through appropriate contracts, that plant breeders' intellectual property rights over the transferred material are respected. Unlike most sugarcane quarantines that are essentially used to import sugarcane germplasm into a country, Visacane can import and export varieties from and to most sugarcane growing countries in the world, ensuring that the material is free from any important pest and disease causing pathogen. Until recently, the sugarcane quarantine process was aimed at detecting known pathogens harbored by the plant material and eliminating these pathogens whenever possible. It is an a priori process, because it only takes into account the pathogens that have been previously described and for which efficient detection tools exist. During the last three decades, several new viruses infecting sugarcane have been discovered, including Sugarcane bacilliform virus, Sugarcane yellow leaf virus, Sugarcane streak mosaic virus and the virus associated with Ramu stunt. In addition, the etiology of chlorotic streak, a disease known since 1929, has not been elucidated so far, although there is evidence for its infectious nature. Therefore, it can be assumed that unknown pathogens are still to be discovered in sugarcane, especially if these pathogens do not cause symptoms that can be easily observed. For these reasons, the research team associated with Visacane is setting up a new strategy of diagnostics, the so-called sequence-independent approach which aims at deciphering the virome (= the genomes of all the viruses that inhabit a particular organism). We believe that our forthcoming combined process, that will include our traditional approaches in addition to the metagenomics approach, will drastically improve our routine quarantine diagnostics. (Texte intégral

Using a high fidelity CCGT simulator for building prognostic systems

Pressure to reduce maintenance costs in power utilities has resulted in growing interest in prognostic monitoring systems. Accurate prediction of the occurrence of faults and failures would result not only in improved system maintenance schedules but also in improved availability and system efficiency. The desire for such a system has driven research into the emerging field of prognostics for complex systems. At the same time there is a general move towards implementing high fidelity simulators of complex systems especially within the power generation field, with the nuclear power industry taking the lead. Whilst the simulators mainly function in a training capacity, the high fidelity of the simulations can also allow representative data to be gathered. Using simulators in this way enables systems and components to be damaged, run to failure and reset all without cost or danger to personnel as well as allowing fault scenarios to be run faster than real time. Consequently, this allows failure data to be gathered which is normally otherwise unavailable or limited, enabling analysis and research of fault progression in critical and high value systems. This paper presents a case study of utilising a high fidelity industrial Combined Cycle Gas Turbine (CCGT) simulator to generate fault data, and shows how this can be employed to build a prognostic system. Advantages and disadvantages of this approach are discussed

On-line transformer condition monitoring through diagnostics and anomaly detection

This paper describes the end-to-end components of an on-line system for diagnostics and anomaly detection. The system provides condition monitoring capabilities for two in- service transmission transformers in the UK. These transformers are nearing the end of their design life, and it is hoped that intensive monitoring will enable them to stay in service for longer. The paper discusses the requirements on a system for interpreting data from the sensors installed on site, as well as describing the operation of specific diagnostic and anomaly detection techniques employed. The system is deployed on a substation computer, collecting and interpreting site data on-line

Multi-agent systems for power engineering applications - part 1 : Concepts, approaches and technical challenges

This is the first part of a 2-part paper that has arisen from the work of the IEEE Power Engineering Society's Multi-Agent Systems (MAS) Working Group. Part 1 of the paper examines the potential value of MAS technology to the power industry. In terms of contribution, it describes fundamental concepts and approaches within the field of multi-agent systems that are appropriate to power engineering applications. As well as presenting a comprehensive review of the meaningful power engineering applications for which MAS are being investigated, it also defines the technical issues which must be addressed in order to accelerate and facilitate the uptake of the technology within the power and energy sector. Part 2 of the paper explores the decisions inherent in engineering multi-agent systems for applications in the power and energy sector and offers guidance and recommendations on how MAS can be designed and implemented