Redundant Sensor Channel Control Using Kalman Bias Isolation
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Solution Overview
Problem
Existing aircraft engine control systems cannot accurately locate a bias or drift in one of the channels for measuring redundant sensors, leading to potential continued use of erroneous measurements during 'cross check' failures.
Innovation Solution
A control system utilizing a Kalman filter observer to determine the bias estimations of redundant sensor channels, allowing for the selection of a healthy measurement channel and exclusion of faulty ones from the control command.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a bank of Kalman filters with residuals is used to detect sensor failures, then the ability to detect failures is improved, but the complexity of the system increases
Solution Approach 1:
The patent segments the failure detection problem by creating separate evaluation modules for each sensor channel. Each channel's measurement is independently evaluated against the Kalman filter estimate, allowing individual channel failure detection without requiring a complete bank of filters for each sensor type.
Solution Approach 2:
The patent introduces an intermediary evaluation mechanism that uses the Kalman filter's state estimates as a reference truth. Instead of directly comparing multiple sensor readings, the system uses the Kalman filter's predicted values as an intermediate reference point to evaluate each sensor channel's validity.
2Productivity
If arbitrary selection of measurement channels is performed during cross-check failure, then the control system can continue operating, but the risk of using erroneous measurements increases
Solution Approach 1:
The patent implements feedback by continuously monitoring the difference between each sensor channel's measurement and the Kalman filter's estimated value. This feedback mechanism allows the system to dynamically identify and exclude faulty channels while maintaining operation with healthy channels, rather than using arbitrary selection.
Solution Approach 2:
The system performs self-diagnosis by automatically evaluating the validity of each measurement channel through comparison with the Kalman filter estimates. The control system serves itself by identifying and excluding faulty sensors without external intervention, maintaining both productivity and reliability.
Data Source
AI summary
System for controlling a device provided with at least one equipment item, the control system comprising at least one sensor capable of measuring operating quantities of the device, and two specific channels for measuring a redundant sensor for each equipment item, at least one embedded control means configured to determine a command intended for at least one equipment item as a function of the at least one measurement of the operating quantity of the device and a selected measurement of the controlled equipment item, the control system further comprising a calculating means configured to determine the selected measurement of the at least one controlled equipment item, by means of a Kalman filter observer, as a function of the at least one measurement of the operating quantity of the device and the measurements of the two specific channels for measuring a redundant sensor for the controlled equipment item.