Gas Turbine Sensor Override Detection via Statistical Analysis
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Solution Overview
Problem
Current methods for monitoring turbine engines are hindered by time delays in fault detection and corrective actions, leading to undesirable shutdown and repair times due to failed temperature sensors, which can cause unsafe operating conditions and increased emissions.
Innovation Solution
A system utilizing existing temperature sensors to detect jumpered sensors through on-site and remote monitoring systems, analyzing signal pairs for mean and standard deviation to identify potential overrides, enabling real-time monitoring and alarm generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional temperature sensor monitoring is used, then safety monitoring is provided, but time delays occur in fault detection and corrective actions leading to extended shutdown and repair times
Solution Approach 1:
The system performs preliminary analysis of temperature sensor signals by continuously calculating mean and standard deviation values to establish baseline patterns before faults occur. This allows the monitoring system to detect anomalies and trigger alerts before critical failures happen, enabling preventive maintenance rather than reactive repairs, thus reducing overall shutdown time while maintaining safety monitoring.
2Reliability
If temperature sensors are used to monitor exhaust gas temperature, then safety monitoring is enabled, but failed sensors require shutdown and repair or reduced operating loads
Solution Approach 1:
The system implements continuous feedback monitoring by analyzing temperature sensor signals in real-time, calculating statistical parameters (mean and standard deviation), and comparing them against established patterns. When a sensor failure or override is detected through this feedback mechanism, the system can alert operators to replace only the specific failed sensor rather than shutting down the entire gas turbine, thereby maintaining operating load and productivity while ensuring safety.
3Productivity
If operators provide false data for failed temperature sensors to override the monitoring system, then the gas turbine can continue operating, but the system runs in potentially unsafe conditions
Solution Approach 1:
The system introduces an intermediary analysis layer that processes temperature sensor signals before they reach the control system. By calculating mean and standard deviation values and analyzing signal patterns, this intermediary layer can detect when a failed sensor is being overridden with false data from another sensor. The system compares the statistical characteristics of the override signal against expected patterns, allowing it to identify potential safety issues while the gas turbine continues operating, thus maintaining productivity without compromising reliability.
Data Source
AI summary
A gas turbine engine system for detecting control sensor override includes a plurality of temperature sensors coupled to the gas turbine engine system. The temperature sensors are configured to generate a plurality of signals representative of exhaust gas temperatures of the gas turbine engine. The system includes an on-site monitoring system coupled in communication to the plurality of temperature sensors. The on-site monitoring system has a processor programmed to continuously receive the plurality of signals from the temperature sensors. In addition, the processor is programed to analyze the plurality of signals to verify the accuracy of the exhaust gas temperatures associated with the plurality of signals, and to detect a jumpered temperature sensor of the plurality of temperature sensors.