Industrial implementation of intelligent system techniques for nuclear power plant condition monitoring

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<ul><li><p>ysgow</p><p>a r t i c l e i n f o</p><p>Keywords:NuclearCondition monitoringAgglomerative hierarchical clusteringRule-based reasoning</p><p>core condition can be gained frommonitoring data obtained duringrefuelling operations. These refuelling events occur muchmore fre-quently than outage inspections, but the raw data requires signif-icant interpretation effort to provide meaningful results. Theapplication of intelligent systems can aid this process, providinga repeatable and reliable method of automatically assessing refuel-ling data. In addition, intelligent system techniques can be applied</p><p>with more technical detail concerning the refuelling process andthe associated monitoring data. The ageing process of nucleargraphite, from which the major components of the reactor coreare constructed, is also described. The second section deals withthe use of intelligent analysis techniques to support various as-pects of analysing refuelling data, and how the application of thesetechniques can also provide valuable understanding into long-termtrends in the data. These trends can then support continued oper-ation and lifetime extension of the Advanced Gas-cooled Reactor(AGR) Nuclear Power Plant (NPP) eet in the UK. The nal section</p><p> Corresponding author.</p><p>Expert Systems with Applications 39 (2012) 74327440</p><p>Contents lists available at</p><p>w</p><p>.eE-mail address: (G.M. West). 2012 Elsevier Ltd. All rights reserved.</p><p>1. Introduction</p><p>As the AGR stations in the UK age, there is an increasing need tounderstand the condition of the reactor core, the major life-limitingcomponent in an AGR station. Inspections undertaken during rou-tine outages, every two-three years, provide high delity informa-tion on a limited number of channels. Additional information about</p><p>to large volumes of this data to uncover trends, which relate to theage and degradation of the graphite core. These trends can be usedto supplement existing understanding of the ageing process of nu-clear graphite and supports the case for continued and extendedoperation of the AGR NPPs.</p><p>This paper is split into the following sections. Firstly a briefintroduction to Nuclear Power Generation in the UK is given along0957-4174/$ - see front matter 2012 Elsevier Ltd. Adoi:10.1016/j.eswa.2012.01.107a b s t r a c t</p><p>As the nuclear power plants within the UK age, there is an increased requirement for condition monitor-ing to ensure that the plants are still be able to operate safely. This paper describes the novel applicationof Intelligent Systems (IS) techniques to provide decision support to the condition monitoring of NuclearPower Plant (NPP) reactor cores within the UK. The resulting system, BETA (British Energy Trace Analysis)is deployed within the UKs nuclear operator and provides automated decision support for the analysis ofrefuelling data, a lead indicator of the health of AGR (Advanced Gas-cooled Reactor) nuclear power plantcores. The key contribution of this work is the improvement of existing manual, labour-intensive analysisthrough the application of IS techniques to provide decision support to NPP reactor core condition mon-itoring. This enables an existing source of condition monitoring data to be analysed in a rapid and repeat-able manner, providing additional information relating to core health on a more regular basis thanroutine inspection data allows. The application of IS techniques addresses two issues with the existingmanual interpretation of the data, namely the limited availability of expertise and the variability ofassessment between different experts. Decision support is provided by four applications of intelligentsystems techniques. Two instances of a rule-based expert system are deployed, the rst to automaticallyidentify key features within the refuelling data and the second to classify specic types of anomaly. Clus-tering techniques are applied to support the denition of benchmark behaviour, which is used to detectthe presence of anomalies within the refuelling data. Finally data mining techniques are used to track theevolution of the normal benchmark behaviour over time. This results in a system that not only providessupport for analysing new refuelling events but also provides the platform to allow future events to beanalysed. The BETA system has been deployed within the nuclear operator in the UK and is used at boththe engineering ofces and on station to support the analysis of refuelling events from two AGR stations,with a view to expanding it to the rest of the eet in the near future.b EDF Energy Barnett Way, Barnwood, Gloucester GL4 3RS, UKIndustrial implementation of intelligent splant condition monitoring</p><p>G.M. West a,, S.D.J. McArthur a, D. Towle ba Institute for Energy and Environment, University of Strathclyde, 204 George Street, Gla</p><p>Expert Systems</p><p>journal homepage: wwwll rights reserved.stem techniques for nuclear power</p><p>G1 1XW, UK</p><p>SciVerse ScienceDirect</p><p>ith Applications</p><p>lsevier .com/locate /eswa</p></li><li><p>tain known issues. The inspection campaign provides very detailedinformation on the health of the core, but based on a limited num-ber of channels.</p><p>As the nuclear power plant ages, there is a greater pressure toincrease the volume and periodicity of these inspections. Inspec-tions are costly, however, as the reactor must be ofine (and thusnot generating electricity) and the fuel channel to be inspectedtemporarily emptied of fuel. Limitation on buffer storage space re-stricts the number of channels that can be empty at a given timeand movement of fuel between the reactor and the store is a timeconsuming process. One approach to mitigate the need for some ofthe increased inspections is to increase the amount of online mon-itoring that is undertaken. One existing source of monitoring datathat can provide information relating to the current channeldimensions is fuel grab load trace data, gathered during refuellingoperations. This condition monitoring data needs to be analysed toprovide meaningful results, which is a labour intensive processrequiring specialised knowledge. IS techniques have been success-fully applied to address this issue and is a key contribution of thiswork.</p><p>2.4. Fuel grab load trace online monitoring data</p><p>AGR stations are refuelled on a regular basis, with the fuel for a</p><p>ith Adescribes the industrial implementation of these techniques in adecision support system that aids the analysis of refuelling eventdata for two NPPs in the UK.</p><p>2. Background</p><p>2.1. Condition monitoring of nuclear power plants</p><p>Within the UK, the existing eet of AGR NPPs are approachingthe end of their originally anticipated design lifetimes. ConditionMonitoring (CM) of the reactors is playing an increasing role inthe continued safe operation of the plant as well as contributingto the safety case made for extended operation beyond the originaldesign lifetimes. This increase in condition monitoring activitygenerates a large volume data that must be analysed. The expertiserequired to analyse this data is limited to just a few experts andtherefore the use of intelligent system techniques to provide auto-mated decision support ensures that this expertise can be utilisedmore widely, and that some of the routine, labour intensive analy-sis can be reduced.</p><p>2.2. Nuclear power generation in the UK</p><p>Currently, approximately 20% of the UK electricity demand ismet by generation from NPPs. The vast majority, seven out of theeight NPPs, are the second-generation AGR designs. These NPPsare approaching the end of their initially intended design lifetimesof 35 years, though some of them have been granted a lifetimeextension of a further 5 years. Part of this process of obtaining a li-cense to operate past the initial design lifetimes is the presentationof a safety case to the regulator, the Nuclear Installations Inspec-torate (NII). According to NII technical guidelines (Boyle, 2002),the safety case is described as:</p><p>. . . the totality of documented information and argumentsdeveloped by the licensee, which substantiates the safety ofthe facility, activity, operation or modication. It provides awritten demonstration that relevant standards have been metand that risks have been reduced so far as is reasonably practi-cable (SFAIRP)</p><p>One method to ensure risk reduction is to undertake analysis ofcondition monitoring data to provide an improved understandingof the current health of the NPP, and in particular the graphite core.The work described in this paper aims to support this goal.</p><p>2.3. Reactor core construction</p><p>With AGR nuclear power plants the dominant life-limiting fea-ture is probably the condition of the graphite core. The function ofthe graphite core is to act as a moderator for slowing the fast neu-trons during the nuclear reaction and to provide a structure that al-lows un-impeded movement of both fuel and control rods as wellas adequate cooling of both the fuel and the graphite moderator.The core is constructed from columns of graphite bricks that formvertical channels for fuel assemblies, control rods, instrumentationchannels and coolant ow. Though the exact conguration changesfrom station to station, approximately 19,000 bricks comprise thecore, which are spread over 12 layers, resulting in over 300 fuelchannels per core. Fig. 1 shows a photograph showing the arrange-ment of the graphite fuel bricks during construction. The materialproperties of graphite change due to neutron irradiation and radio-lytic oxidation encountered in the reactors, during normal opera-</p><p>G.M. West et al. / Expert Systems wtion. This affects the dimensions, internal stress and integrity ofthe graphite bricks, which in turn could impede the movement offuel, control rods and coolant through the core. Knowledge of thecurrent dimensions of the graphite bricks that comprise the coreis therefore a key requirement of understanding the current condi-tion of the core. These dimensions are routinely obtained frominspecting the core during outages. Typically, every three years areactor will undergo an outage where a limited number (currently31 for the oldest reactors, though much less for the younger reac-tors) of fuel channels are inspected. Inspection includes visualinspection of the channel walls using special TV camera equip-ment, accurate measurement of the diameter and tilt of the chan-nel bore across the fuel height of the channel, and trepanning smallsamples of the core which are then subject to a series of materialproperties tests. Selection of these channels for inspection isundertaken to ensure a representative subset of the whole core isobtained, as well as targeting individual channels which may con-</p><p>Fig. 1. Photograph showing the layout of the reactor core during constructionshowing the arrangement of a layer of graphite fuel bricks. Picture courtesy of EDFEnergy Ltd.pplications 39 (2012) 74327440 7433single channel lasting approximately 67 years. The uranium fuelis housed within refuelling assemblies that are inserted into a fuelchannel that has been evacuated during the refuelling process.</p></li><li><p>whereby limits could be tailored to individual stations, new defectshapes could be easily added, and also so that the results could be</p><p>ith ATypically the reactors are refuelled in batches, with 810 fuelassemblies being exchanged every 68 weeks (Ziver et al., 2004).A full description of the fuel assembly can be found in Ng (1995),but the point of interest here is that the fuel assembly contains setsof stabilising brushes that guide the fuel assembly through thecore. As the fuel assembly is lowered into the core, these brushesform an interference t with the fuel channel wall, and as a resulta friction force is generated. During refuelling a load cell recordsthe apparent weight of the fuel assembly along with a measure-ment of position into the core. Changes in the dimension of thechannel, such as those caused by known features such as the pistonseal bore, the guide tubes and the stand pipes, as well as changescaused by ageing and distortion of the graphite itself will resultin a change in the frictional component of the measured load.The measured load over the course of a refuelling operation istermed the Fuel Grab Load Trace (FGLT) and this can provide infor-mation relating to the current health of the core. These FGLT tracesare manually assessed by an expert who has built up an under-standing of what constitutes a normal FGLT through years of expe-rience, supported by a theoretical understanding of the refuellingprocess and experimental rig-work and simulation to generateproles of anomalous behaviour (Roscow, Skelton, &amp; Mclachlan,2008). Following every refuelling campaign, these FGLT are manu-ally analysed and the results are fed into a quarterly MonitoringAssessment Panel (MAP) meeting, where the results of analysisare compared with other sources of monitoring data such as ther-mal to neutron power ratios (Haddock &amp; Parks, 1995) and controlrod movements (Wallace et al., 2010) to determine whether thereis any indication of anomalous behaviour which might suggestcore distortion.</p><p>Two issues with the manual analysis of FGLT are:</p><p>1. The paucity of expertise. Knowledge and understanding of whatconstitutes a normal FGLT and how anomalous core behaviourmay manifest itself in the FGLT is limited to only a few experts.As the volume of condition monitoring data that is required tobe analysed increases, a greater burden is placed on this limitedresource.</p><p>2. Manual analysis is based on human judgement. Differentexperts may interpret the raw data slightly differently. Thoughanomalous behaviour is discussed with a wider pool of exper-tise, conicts may arise particularly with borderline cases.</p><p>The application of intelligent system techniques addressesthese two issues by providing a captured and encoded version ofthe human expertise which can be applied to provide a repeatableand auditable diagnosis of FGLT data, thus supporting, but impor-tantly not replacing, the decision process of the human expert.</p><p>2.5. Related work</p><p>The application of intelligent systems to problems in the nucle-ar domain is well reported, for example (Beck &amp; Behera, 1993) re-ports over one hundred applications of expert systems to thenuclear domain, though many of the articles describe proposedconcepts and prototype systems rather than industrial deploy-ment. None of these relate directly to graphite core condition mon-itoring and the analysis of FGLT, though previous work has seen thedevelopment of ALTA, an intelligent system for the analysis of FGLTto determine whether fuel has set down correctly in the bottom ofthe core (Steele et al., 2003). ALTA used a combination of C4.5,Kohonen Networks and K-means clustering to establish the loca-tion of the fuel touchdown point and has implemented a rule-</p><p>7434 G.M. West et al. / Expert Systems wbased system to assess the set down process to ensure that eachstage has been completed successfully. This work established thatFGLT could be analysed to provide information relating to fueleasily explained through presentation of...</p></li></ul>


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