CJSC ROTEC's competence

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2 CJSC ROTEC's competence During the power genera4ng unit opera4on the analysis of the occurring processes in their influence on technical condi4on of the equipment and its parts is not performed. A system of the equipment performance monitoring and equipment life evalua4on is created for execu4on of such analysis. Lower CHP sta3on level Data signals 1 Gas turbine CJSC ROTEC's lower level server Data transmission to CJSC ROTEC's RMDC CHP sta4on opera4ng personnel 6 2 Analyst's recommend a4ons and test schedule by expert of CJSC ROTEC Processed data CJSC ROTEC's upper level server 3 CHP sta4on feedback Analyst of CJSC ROTEC 5 Communica4on with opera4ng personnel Upper level - Remote Monitoring and Diagnos3cs Centre (RMDC) of CJSC ROTEC The remote monitoring system (RMS) consis4ng of individual so;ware/hardware func4onal elements determines the remaining life of monitored facility's elements and systems and the schedule of interac4on of RMC personnel with the Customer when the monitored facility is restored. 4 Informa4on about defects Expert of CJSC ROTEC 2

3 Evaluation of the remaining life of assemblies and parts Possibility to evaluate the remaining life of each listed part at any 4me. 3

4 Model construction methods The Remote Monitoring System analy4cal component so;ware provides a wide range of facili4es for simula4on of complex processes (neural network methods, method of principal components, method of mul4- dimensional Monte- Carlo modelling) which enables an expert to select the best model construc4on method and off- standard turbine performance criteria. Method of principal components Neural network methodology Mul3- dimensional state evalua3on technique (MSET) 4

5 Discrepancies of two different models Con4nuous comparison of 2 values: characteris4c specified in the manufacturing plant's opera4on manual and current 4me readings of the physical model Empirical model and discrepancy between its reading and the current value of ac4ve power enable monitoring the slightest data signal devia4on, avoiding its unplanned change Dependence from the opera3on manual Ac3ve power (sensor signal) Physical model at the current 3me Reading of ac3ve power empirical model Dynamic boundary Dynamic envelope Physical model discrepancy Empirical model discrepancy 5

6 Analysis of causes of discrepancy between the model and the fact Devia4ons or "discrepancies" of "empirical" and "determinis4c" models from the parameters measured at the facili4es beyond the permissible limits are analyzed by discrepancy interpreters which determine the causes of any facility performance change and their localiza4on automa4cally. Input model parameters ranged in terms of their influence degree Graphic dependencies of the input model parameters 6

7 Vibration change - active defect development stage An accident which could have been avoided Any break of the 4ght fixng bolts of turbine T HPR- MPR coupling would be detected by UTW's RMDS at least 9.5 hours before the accident The beginning of the support vibra4on change 9.5 hours before the accident CJSC ROTEC's RMDS: forecasts behavior of systems, elements and parts at 90% mathema4cally calculated probability. It detects, for example: Destruc4on of turbine rotor coupling flange 9 6 hours before the accident. Destruc4on of external chamber element (cone, plate) 3 1 hours before the accident. Change of vibra4on padern of the turbine within 30 to 80 seconds a;er the vibra4on beginning. Defec4ve ARS within 30 seconds a;er the event occurrence. At any 4me the remaining life of the turbine set systems or elements: - before accident; - before the next scheduled maintenance; - before the end of the lifecycle. Also CJSC ROTEC's RMDS allows forming the replaceable, repairable parts spectrum and the op4mum 4me of repairs at any 4me, taking into considera4on of the state of turbine plant, dispatch opera4on schedule and warehouse logis4cs. 7

8 Determination of remaining life The residual life is calculated using the principle of "performance- dependent safe opera4on" based on the key parameters, any change of which (individual or group change) results in a non- opera4onal or limit state of the facility. 4 months before accident Before triggering of safety alarm 3 months before failure 2.5 months before repair Protec4on, emergency shutdown Before triggering of alarm Process parameter Alarm system 1. Monitored parameter in model predic4on zone 3. Determina4on of a defect, parts logis4cs 2. Discovered devia4ons Scheduled repair Accident forecast! Tradi4onal RMS opera4on: detec4on of a defect a;er alarm triggering; an unscheduled shutdown is necessary for elimina4on of the defect 4. Elimina4on of a defect during scheduled repair, before the parameter falls outside the alarm and protec4on triggering levels October November December January February March April Early defect and failure detec4on features enable professionals of CJSC ROTEC to reveal any problems before they turn to catastrophes, poten4ally saving thousand million roubles of customer's funds. 8

9 Forecasting Ac3ve power Regression A forecas4ng func4on is implemented in CJSC ROTEC's RMDS, the professional having an op4on of evalua4ng both short- term (the nearest 15 to 30 min.), and long- term (1 to 5 or 7 years) forecast. Alarm boundary Ac3ve power (empirical module) Safety alarm boundary To long- term forecast Ac3ve power discrepancy (archive values) Upper dynamic boundary The current value of the ac3ve power discrepancy Regression Lower dynamic boundary 9

10 Influence of diagnostics operations on the equipment performance Timing of opera3ons: Change of diagnos4c parameters of the equipment opera4on (vibra4on, temperature, noise, leaks, geometry, lubrica4on quality) in reference points, automated archive logging Turbine unit performance evalua4on and issue of recommenda4ons on elimina4on of causes of any detected devia4ons to maintenance services and recommenda4ons on adjustment of opera4on mode to opera4ng personnel Another measurement of diagnos4c parameters of the equipment opera4on Evalua4on of the turbine unit performance, determining - the influence of run 4me between parameter measurements - influence (evalua4on) of quality of maintenance services' ac4vity on elimina4on of causes of detected performance devia4ons in the preceding cycle - influence (evalua4on) of equipment opera4on quality over the elapsed period Issue of recommenda4ons on elimina4on of causes of any detected devia4ons to maintenance services and recommenda4ons on adjustment of opera4on mode to opera4ng personnel Years 4 to 6 cycles of equipment monitoring opera4ons are required for beginning of consistent performance improvement, and a;er 10 to 12 cycles the maximum reliability and life will be ensured for opera4on of the whole fleet. An addi4onal advantage is the con4nuous improvement of opera4on and repair and maintenance system. 10