Experience with Hydro Generator Expert Systems

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An insight on the set-up and uses of Hydro Generator Expert Systems

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Experience with Hydro Generator Expert Systems

  1. 1. GE EnergyExperience withHydro GeneratorExpert SystemsAs presented at the Iris Rotating Machine ConferenceJune 2008, Long Beach, CAPeter Lewis, IrisJohn Grant, GE EnergyJ. Evens, NYPA
  2. 2. GE Energy | GER-4488 (07/08)
  3. 3. Experience with Hydro Generator Expert SystemsCurrent technological advances in condition monitoring are monitors suitable for this hydro-generator monitoring [1]. In the caseemploying an increasing number of complex sensors and of partial discharge monitoring, where no solution existed, aadvanced monitors to diagnose the operating status and condition cooperative R&D effort between NYPA and Iris Power led to theof hydro generators and turbines. Advanced systems routinely development of a cost effective on-line PD monitor calledemployed may include bearing vibration, air gap, partial discharge, HydroTrac™ [2].and flux monitoring. Proper interpretation of this often complex Knowledge Baseinformation can lower operating and maintenance expenses, in One of the first diagnostic expert systems for on-line turbo-generatoraddition to reducing unscheduled outages and catastrophic monitoring was developed in the 1980s by EPRI and was calledfailures. However, the volume of available data from these GEMS [3]. Although a later attempt to create a commercial systemmonitors, and the extensive interpretation necessary to evaluate based on this research prototype failed, many of the machinethe complex waveforms and spectrums, can overwhelm plant behavior models developed for GEMS were later very relevant topersonnel and resources. Sophisticated software and algorithms HydroX. In addition, this system clearly demonstrated the need forare often necessary to correlate and interpret this data to establish some form of probabilistic reasoning as complex machine monitoringthe overall generator and drive train condition. is never fully deterministic. The technical success of GEMS spawnedHydroX™ (for Hydro Expert) is a knowledge-based expert system follow on work by EPRI and others in the area of hydro generatorprogram for on-line monitoring of hydro-generators. Working with monitoring [4].the New York Power Authority, the system was developed over five Recognizing the loss of machines expertise in the hydro industry,years by Iris Power and GEs Bently Nevada* team. After a further in the late 1990s NYPA initiated a research project to interviewtwo years of prototype evaluation at NYPA’s St. Lawrence Power generator design, operations, and maintenance personnel toProject on two 60 MVA generators, the validated system is now document a diagnostic rule set for an expert system like HydroX.commercially available. Although at the time, suitable monitors and sensors were still underThe successful development of HydroX was predicated by several key development, and no suitable software platform existed, it was feltfactors, including: that documenting the rules was a critical first step. This was a multi-1. Available and cost effective on-line monitors for critical year effort using experts from OEMs, industry, academia, and utility components of the turbine and generator. engineering and operations staff. The result of this project was the2. Expertise in the form of hydro-generator design, operation, knowledge base that was used later to create HydroX. and maintenance knowledge that could be codified into expert system rules. Expert System Tools3. A suitable commercial software platform or expert system shell. Since the 1980s, expert systems have been a topic of research aimed at automating monitoring and diagnostics for complex4. A site where the system could be deployed and evaluated. industrial equipment. Early attempts involved the use of specializedEach of these factors is discussed below in greater detail. computer hardware and software which were not robust or ready for industrial applications. With the growth in popularity andOn-line Monitors capabilities of desktop PCs, it became possible to developAs part of an upgrade and life extension project of their hydraulic distributed client-server applications. During the 1990s a prototypefleet which began in the late 1990s, NYPA identified several key system called ACMS (Advance Condition Monitoring System) wastechnologies necessary to more completely monitor a large hydraulic fielded on such a platform but proved too unreliable, slow, andturbine and generator. In some cases, although on-line monitors were difficult to configure to be commercially viable. Other vendorsavailable, their cost or complexity made them prohibitive for inclusion developed expert system shell programs [5] however, these systemsinto an expert-based monitoring system like HydroX. As well as the suffered from a lack of standard interfaces to sensing andnormal process data, specialized monitors that were considered monitoring systems. During this period vendors tended to createcritical to the expert system diagnostics include on-line air-gap,bearing vibration, stator partial discharge and core temperature and islands of technology which were incapable of communicatingvibration. Over time, competition in the market place led to several with each other.GE Energy | GER-4488 (07/08) 1
  4. 4. Only in the past few years have practical PC-based tools been HydroX Featuresavailable for development and commercial deployment of expert HydroX is a condition-based diagnostic system for hydro-turbine/system based plant monitoring systems. System 1* is such a tool, generators. The system is based on a commercial PC-based assetand contains standard interfaces such as OPC clients/servers management tool called System 1. System 1 is a distributed softwarewhich allow it to communicate with external third party monitors product based on a SQL Server database and contains components forand sensors. In addition, it contains a rule based inference engine data collection from remote systems via OPC, a production rule engine forand provides tools for users to develop decision based logic. processing user defined rules, and a design tool for developing and testingSystem 1 also provides a number of analysis and visualization tools rules and developing custom user interfaces. The rules are the basis for thethat enhance the rule engine by allowing end-users to view data HydroX System and represent the knowledge base of the expert system.(historical and current) and rule results in a variety of ways. Individual rules were created to process input data into more useful relevant data. Processed data is than fed through various analysis algorithmsEvaluation Site embedded in rules again, or to provide decision support. Often multiple rulesAn ideal time to install the sensors/monitors necessary to support are created and grouped into “Rulepaks” that are meant to provide specifica system like HydroX is during a plant refurbishment/upgrade. At analysis functionality. In this manner, an expert system can be created thatthe St. Lawrence Power Project, NYPA was undertaking a plant life can encode expert knowledge into an automated analysis system.extension project sequentially on 16 units and this project providedthe perfect platform for evaluating the HydroX rule-set. During Utilizing the knowledge base developed earlier with NYPA, aeach unit’s upgrade, additional sensors were installed to support modular set of HydroX Rulepaks were created in System 1.the expert system and interfaces to the plant control and Encoding each major sensor group in its own Rulepak facilitatedmonitoring systems were created. Using the acquisition portion of the customization of HydroX for the available machine sensor dataHydroX, data was collected from these systems over time on at different sites. If a particular monitor such as PD is not available,several units, making it possible to identify machine specific then the rules dealing with those inputs can be easily removed,behavior and characteristics. The generalized rule-set created leaving the rest of the system functional. Some Rulepaksduring the knowledge base development was then customized incorporate corroboration algorithms that can communicate withthrough a “tuning” algorithm. These tuning rules were created to other Rulepaks in order to raise confidence in a diagnosis. In thisaccount for specific generator behaviors due to subtle differences manner HydroX offers a comprehensive system that can drawin manufacture or external factors such as seasonal changes in upon multiple data paths to reinforce its diagnostic accuracy. Theambient conditions. addition of more monitoring systems often will lead to a better diagnosis.Software Components One particular challenge in any expert system is dealing with uncertainty in the data analysis. System 1 has built-in mechanisms HydroX RulePak System 1 Config HydroX Display for indicating the severity of a problem. In HydroX this was extended to utilize a Mycin like uncertainty scheme [6] to combine System 1 Platform and Database facts from various sensor inputs into a diagnosis with a certainty factor. As sensor readings vary further from expected values, or multiple indications of a problem become apparent, the certainty System 1 Data Acquisition in the diagnosis of a fault condition increases. Where possible, the prediction of “expected” value for sensors is Bently 3500 made based on mathematical models of machine parameters that are then tuned for the specific unit. These predicted values are GCS Computer SCADA Computer HydroTrac Controller then compared to the actual measured values and deviations areFigure 1. System 1 components analyzed by the rules to compute a diagnosis. For example, the2 GE Energy | GER-4488 (07/08)
  5. 5. predictions of thrust bearing pad temperatures are made based on be expected depending on the machine state. HydroX uses thisthe thrust bearing oil temperature and the MW load of the information to set mode-specific thresholds for alarms making themachine. This basic equation is then customized to account for system very sensitive to small variations in readings.heating/cooling time constants of the machine with load, and to The machine mode is also used in several instances to calculatethe actual readings obtained at full load for each sensor which and alarm on the trend of sensor values. The trend of nominal airvary due to sensor location and other physical properties. gap, during field flashing for example, can indicate a specific type of problem that trending at nominal machine load would not detect.Figure 2. Graph showing comparison of actual and predicted bearing vibrationbased on unit load and bearing oil temperature Figure 4. Trend plot of measured air-gap changes during a startup at NYPAFor many sensors, the alarm thresholds may be significantlydifferent depending on the mode of the machine. HydroX has rules Current industry trends are to move to more automated plants,to determine the machine mode and where necessary, different with less on-site expertise and operations staff. As describedthresholds and even rules are executed dependent on this mode. above, HydroX can calculate and trend key features and synthesizeThe specific modes HydroX recognizes are: standstill, mechanical summary indications from complex data sets from monitors suchrunup/rundown, rated-speed de-energized field, field energized but as vibration, air-gap, PD, etc. Using these intermediate indicators,unsynchronized, synchronized unloaded, load transient and loaded along with diagnostic rules, an expert system like HydroX can filterthermally stable. An example of this behavior would be air gap and focus attention to abnormal values, and provide diagnosis ofmeasurements, where significantly different nominal air gaps can specific faults as well as possible remedies. In addition, trending of such parameters over years can indicate long-term degradation that may otherwise go undetected until damage limits are breached. NYPA Installation As part of a plant modernization project, Unit 18 at the St. Lawrence Power Project was removed from service to be refurbished/up-rated. During this work, additional sensors and monitors were installed to instrument the unit for HydroX. In addition to the conventional unit monitoring connected to theFigure 3. Depiction of expected air gap trend for different machine statesGE Energy | GER-4488 (07/08) 3
  6. 6. Figure 5. HydroX sensor setplant control system, additional sensors and monitors were added is that since the units are coming off a major overhaul, the numberfor partial discharge, bearing vibration, core vibration, back of core of faults has been minimal. In addition, many of the long-termtemperatures, and air-gap. trending rules for conditions such as partial discharge can takeAs each of the 16 units in the plant are refurbished (a 10-year years to calculate and are just now providing useful values.program), the identical sensor set is installed and connected toHydroX. Once completed, all 16 units will be monitored.A group of two dedicated PC computers run the HydroXcomponents; the data acquisition system, the SQL ServerDatabase, the Diagnostic Rule Engine and the User Interface.These computers were installed on a separate LAN, and interfacedto the other necessary plant systems (Generator Control System toobtain conventional unit sensor data, HydroTrac for PD data, and aBently Nevada 3500 rack for air gap and vibration data). Theinterfaces to external systems were accomplished using an OPCData Interface [7].Experience to date:Over the past several years, the prototype HydroX has been moni-toring Unit 18 (and now several other units as they are refurbishedand instrumented). One difficulty with this approach to deployment Figure 6. HydroX data interfaces4 GE Energy | GER-4488 (07/08)
  7. 7. One significant problem that only became apparent as additional The creation and testing of these rules was a significant and unan-units were connected to HydroX related to the tuning of the rules. ticipated effort, but was clearly necessary if HydroX was to be aThe models and algorithms used to provide predicted sensor val- commercial success.ues require substantial tuning for various constants, which can A similar problem was found with the setting of alarm limits foronly be done once the unit is in service. For the deployment of a measured values. There are a multitude of custom values thatsuccessful commercial system, it is not practical for a Field Service must be set for HydroX to calculate malfunction certainties proper-Engineer to be on-site waiting on a unit start-up, and for possibly ly. These values are usually known by plant personnel and used forweeks after that to collect data for the various machine states basic alarming of critical parameters. There are still many valuesneeded to tune the rules. For this reason, a set of “auto-tuning” that may not be known by plant personnel and also, the sheerrules were written. These rules track data during initial unit opera- multitude of values would make the collection of these values andtion, and automatically calculate and enter the specific constants customization of the system extremely time consuming. In manyneeded for the various predicted sensor values. The rules use linear cases these values can be based on given machine standards.regression to determine the dependency of two independent vari- HydroX was built to address this issue by incorporating an auto-ables on a given sensor input. This dependency is usually calculat- matic tuning system for alarm limits. For example, stator windinged during startup as the machine will see the greatest span of temperature limits are set according to winding insulation classesmeasurements for a given input. (i.e., NEMA), such standards are used in HydroX to automaticallyFigure 7. Partial sample logic of an auto-tuning ruleGE Energy | GER-4488 (07/08) 5
  8. 8. choose the proper limits based on machine construction parame- and experts alike by providing them with real-time, easy toters. HydroX also allows the end-user to set these values manually understand information. By providing automated data collectionand override the automatic values if required. and analysis, the system minimizes the vast volume of data that would otherwise have to be collected and analyzed manually. ThisA final lesson that can be taken from this experience concerns the also leads to a greater wealth of data but without jeopardizing thereliability of the system. In general, a hydro turbine and generator speed and accuracy of analysis as can be the case when too muchis a true model of reliability with some units in continuing service data is present. HydroX also reduces the number of annoyingafter 50 years. Unfortunately the same cannot necessarily be said “nuisance alarms” by providing a corresponding certainty withfor the components used to monitor them. It is far more likely that each diagnosis. It is expected that an expert system like HydroXa sensor, data acquisition system, computer or network will experi- can extend machine life, reduce forced outages, and reduceence a problem than a hydro generator will. Problems with some operation and maintenance expenses.sensors failing and computer components have occurred since theoriginal installation of the system in 2005. Software and operating REFERENCESsystem problems can also occur in any system relying heavily on 1. J.F. Lyles et al, “Using Diagnostic Technology for Identifyingcomputer systems and network interfaces. In particular, plant net- Generator Maintenance Needs”, Hydro Review, June 1993, p. 58.work security has been a source of problems, as network security 2. B.A. Lloyd, S.R. Campbell, G.C. Stone, “Continuous On-line PDbecomes ever more stringent forcing frequent upgrades of soft- Monitoring of Generator Stator Windings”, IEEE Trans EC, Dec.ware, hardware and protocols—all of which may require reconfigu- 1999, p. 1131.ration of the various components in HydroX. 3. G.S. Klempner, A. Kornfeld, and B. Lloyd, “The generator expert monitoring system (GEMS) experience with the GEMS prototype,”Future Plans EPRI Utility Motor and Generator Predictive MaintenanceBased on the successful deployment on two units at St. Lawrence, Workshop, December 1991.a commercial System 1 Rulepak for HydroX has been created. Overtime this system will be installed on all 16 units at St. Lawrence. It 4. A. Roehl and B. Lloyd, “A developing standard for integratingis expected, that during future deployments at other sites, new hydroelectric monitoring systems” EPRI Motor and Generatorinterfaces will be developed to sensors and monitors from other Conference, Orlando, Nov. 1995.vendors. Standardized protocols like OPC make this a relatively 5. Nilsen, S., OECD Halden Reactor Project, Inst. for Energiteknikk;simple effort. Obvious future extensions to the system would be to “Experiences made using the expert system shell G2, Tools forinclude support for pump storage units which are often critical and Artificial Intelligence”, 1990, Proceedings of the 2nd Internationalhighly stressed assets. IEEE Conference, 6-9 Nov 1990, page(s): 520-529Conclusions 6. Rule Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project, BG Buchanan and EHThe HydroX system is an advanced expert system that will help Shortliffe, eds. Reading, MA: Addison-Wesley, 1984utilities protect hydro turbine-generators while reducing the cost ofoperation by transitioning from preventive to condition-based 7. OPC Foundation – www.opcfoundation.orgmaintenance. The system combines advanced fault detection HydroX is a trademark of the New York Power Authority.knowledge from multiple industry experts with modern data HydroTrac is a trademark of Iris Power Engineering, Inc. * Bently Nevada and System 1 are trademarks of General Electric Company.acquisition systems in order to empower maintenance technicians6 GE Energy | GER-4488 (07/08)
  9. 9. NotesGE Energy | GER-4488 (07/08)
  10. 10. GE Energy | GER-4488 (07/08)
  11. 11. GE Energy | GER-4488 (07/08)
  12. 12. ©2008, General Electric Company. All rights reserved.GER4488 (07/08)

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