Aircraft Engine Fault Detection Using Vibration Data
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Solution Overview
Problem
Current engine maintenance programs for airplanes lack effective detection and diagnosis of faults, leading to potential safety issues during flight due to inadequate management of engine problems.
Innovation Solution
A system utilizing vibration sensors to generate virtual input data, estimate model parameters, and calculate covariance of parameter estimation errors, which allows for the detection and diagnosis of faults in airplane engines by comparing test variables and numerator coefficients between nonfaulty and suspicious models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional engine maintenance programs based on manufacturer procedures are used, then engine repair can be performed, but fault detection and diagnosis capabilities are insufficient
Solution Approach 1:
The system performs preliminary fault detection and diagnosis by analyzing vibration data before actual engine failure occurs. The offline model construction and online fault detection workflow enables proactive identification of engine anomalies, allowing maintenance to be scheduled before critical failures happen, thereby improving reliability without requiring complex real-time intervention systems
Solution Approach 2:
The patent introduces vibration sensors as intermediary devices that capture engine vibration signals, and uses signal processing algorithms as mediators to transform raw vibration data into diagnostic information. The offline constructed model acts as an intermediary that bridges the gap between raw sensor data and fault diagnosis, enabling effective fault detection without direct complex hardware modifications to the engine
2Measurement precision
If vibration data analysis is implemented for fault detection, then diagnosis accuracy is improved, but data processing complexity increases
Solution Approach 1:
The system performs preliminary data processing and model construction offline using non-faulty vibration data. By pre-processing the data and constructing reference models beforehand, the online detection phase only requires comparing current vibration data against the pre-established model, significantly reducing real-time processing complexity while maintaining high diagnostic accuracy
Solution Approach 2:
The patent segments the fault detection process into distinct phases: offline model construction phase and online fault detection phase. This segmentation allows complex computational tasks to be performed offline when computational resources are abundant, while online operations focus on simpler real-time comparisons, thereby reducing overall processing complexity without sacrificing accuracy
Data Source
AI summary
A system for detecting and diagnosing a faultive state of an airplane engine, including: at least one vibration sensor attached to an airplane; a reference model database construction unit; and a fault detection and diagnosis unit which estimates a parameter of a model, obtains a test variable and a numerator coefficient value difference of a transfer function between the models, and the covariance of parameter estimation error, and diagnoses the faultive state and the faultive cause of the airplane engine. Accordingly, the present invention can determine the faultive state and the detective cause of the airplane engine using the vibration data of the airplane engine.