Predictive diagnostics of power generating equipment of a power plant
POWER
Objective: Implementation of the software for predictive diagnostics at 11 thermal power plants
Tasks:
Equipment:
Solution
Creation of a defect classifier for power generating equipment with a gas turbine unit:
Results
Tasks:
- Development of diagnostic equipment models based on operating data
- Visualization of the results of mathematical model calculations
- Indication of criteria for deviations, data disruptions, parameter values, equipment and system states compared to normal values (model-based) within a specific operating mode with an indication of the explicit or assumed type of defect
- Visualization of the calculations of diagnostic models of the current state in real-time mode and the expected state in the future, indications of the defect classifier and indicators of the technical condition of the monitored equipment
Equipment:
- Gas turbine
- Gas turbine generator
- Utilization boiler
- Steam boiler
- Hot water boiler
- Steam turbine
- Steam turbine generator
- Boost compressor station
- Power transformers
- Power transmission lines (optional)
- and other equipment
Solution
Creation of a defect classifier for power generating equipment with a gas turbine unit:
- Gas turbine with generator and auxiliary equipment
- Two-stage axial compressor boost compressor station
- Dual-circuit utilization boiler with auxiliary equipment
- Steam turbine unit with auxiliary equipment and generator
Results
- Prevention of forced and emergency shutdowns
- Implementation and testing of software at 1 station
- Scaling to 9 stations
- Scaling to the entire variety of the customer's thermal power plants
Software testing CyberStudio software product for predictive analytics of gas turbines GTES-25PA
MACHINERY
Objective: Exploring the possibility of using predictive models for equipment
Tasks: Creation of a mathematical model for diagnostics of technical condition of gas turbine engines as part of the GTES-25PA in a specialized CyberStudio software.
Equipment: 4 gas turbine engines
Solution
Analysis of historical data of equipment operation and building models of operation of 4 gas turbine engines as part of GTES-25PA in a specialized CyberStudio software.
Results
The models detect a number of anomalies in the data associated with certain works performed on engines, which indicate the development of malfunctions, about the possible change in the characteristics of the system.
This is how the discrepancy is observed in the following models:
Tasks: Creation of a mathematical model for diagnostics of technical condition of gas turbine engines as part of the GTES-25PA in a specialized CyberStudio software.
Equipment: 4 gas turbine engines
Solution
Analysis of historical data of equipment operation and building models of operation of 4 gas turbine engines as part of GTES-25PA in a specialized CyberStudio software.
Results
The models detect a number of anomalies in the data associated with certain works performed on engines, which indicate the development of malfunctions, about the possible change in the characteristics of the system.
This is how the discrepancy is observed in the following models:
- Increases between flushes discrepancy in HEU filter models
- Models respond to non-critical node malfunctions
Software testing CyberStudio software product for predictive analytics of gas turbines GTES-25PA
MACHINERY
Objective: Exploring the possibility of using predictive models for equipment
Tasks: Creation of a mathematical model for diagnostics of technical condition of gas turbine engines as part of the GTES-25PA in a specialized CyberStudio software.
Equipment: 4 gas turbine engines
Solution
Analysis of historical data of equipment operation and building models of operation of 4 gas turbine engines as part of GTES-25PA in a specialized CyberStudio software.
Results
The models detect a number of anomalies in the data associated with certain works performed on engines, which indicate the development of malfunctions, about the possible change in the characteristics of the system.
This is how the discrepancy is observed in the following models:
Tasks: Creation of a mathematical model for diagnostics of technical condition of gas turbine engines as part of the GTES-25PA in a specialized CyberStudio software.
Equipment: 4 gas turbine engines
Solution
Analysis of historical data of equipment operation and building models of operation of 4 gas turbine engines as part of GTES-25PA in a specialized CyberStudio software.
Results
The models detect a number of anomalies in the data associated with certain works performed on engines, which indicate the development of malfunctions, about the possible change in the characteristics of the system.
This is how the discrepancy is observed in the following models:
- Increases between flushes discrepancy in HEU filter models
- Models respond to non-critical node malfunctions
