Air cycle machine failure alert system
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Solution Overview
Problem
Existing aircraft air conditioning and pressurization systems face challenges in predicting failures in Air Cycle Machines (ACMs), which can lead to inadequate air pressure and require emergency landings.
Innovation Solution
A method for predicting ACM failures by calculating changes in energy across the ACM compressor, determining compressor efficiency, and comparing it to a failure prediction model, using sensor measurements and energy transfer calculations between ram airflow and ACM airflow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional ACM systems operate without continuous monitoring, then device complexity is reduced, but reliability deteriorates due to inability to predict failures
Solution Approach 1:
The ACM system performs self-diagnosis by using its own operational parameters (temperatures, pressures, power consumption) to calculate efficiency metrics and detect anomalies. The system monitors itself without requiring external diagnostic equipment, allowing the ACM to identify its own degradation patterns and predict failures before they occur.
Solution Approach 2:
The system continuously monitors ACM operational parameters and provides feedback through efficiency calculations. By comparing real-time efficiency metrics against expected performance ranges, the system generates alerts when degradation is detected, enabling proactive maintenance scheduling and preventing catastrophic failures.
2Loss of time
If ACM failures are detected only after they occur, then measurement precision is reduced, but loss of time increases due to emergency landings
Solution Approach 1:
The system performs preliminary failure detection by continuously calculating ACM efficiency based on operational parameters before actual failure occurs. By establishing baseline efficiency metrics and monitoring for deviations, the system can predict impending failures and schedule maintenance during planned downtime rather than requiring emergency landings.
Solution Approach 2:
The patent replaces direct mechanical inspection methods with a computational approach. Instead of physically inspecting ACM components, the system uses mathematical calculations based on easily measurable parameters (temperatures, pressures, power) to infer the mechanical state and efficiency of the ACM, enabling remote and continuous monitoring.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables early prediction of ACM failures, allowing for proactive maintenance and reducing the risk of unexpected system failures, thereby ensuring safe and comfortable flight operations.
Implementation Method 1
calculating an energy transfer across a heat exchanger between a ram airflow and the ACM airflow
Data Source
AI summary
Disclosed herein is a method for failure prediction in an Air Cycle Machine (ACM). The method includes calculating a change in energy of an ACM airflow passing from an inlet of the ACM compressor to an outlet of the ACM compressor. The method may also include calculating a kinetic energy of the ACM compressor based on calculating the work of the ACM compressor on the ACM airflow as the ACM airflow passes through the ACM compressor, calculating the work of the ACM compressor based on the inlet temperature of the ACM airflow at the inlet of the ACM compressor, compressor pressure ratio of the ACM compressor, and a fluid property of the ACM airflow at the inlet of the ACM compressor. Additionally, the method can include calculating an ACM compressor efficiency as a ratio of the change in energy of the ACM airflow across the ACM compressor to the kinetic energy of the compressor. The method may further include predicting a failure state of the ACM compressor.