Sensor Multiplicative Fault Detection via Virtual Model Comparison
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Solution Overview
Problem
Existing methods for detecting multiplicative faults in sensors within complex systems are inefficient due to difficulty in estimating system parameters and determining faulty sensors, especially in systems with many sensors, leading to unreliable fault detection.
Innovation Solution
A method and device that utilize a Kalman filter and quadratic difference calculations, combined with pass-band and low-pass filtering, to compare target sensor signals with estimated signals from auxiliary sensors, determining the presence of multiplicative faults through ratio comparisons and confirmation parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If system parameters are estimated from sensor detections to detect multiplicative faults, then fault detection capability is improved, but the complexity of parameter estimation and difficulty in determining faulty sensors increases significantly
Solution Approach 1:
The patent creates a virtual model (copy) of the physical system using a mathematical model that replicates system behavior. This virtual model generates estimated sensor signals without requiring complex parameter estimation, allowing fault detection by comparing actual sensor readings against the virtual model's predictions. The virtual copy eliminates the need to estimate difficult-to-determine system parameters while maintaining fault detection capability.
Solution Approach 2:
The patent introduces a virtual model as an intermediary between the physical system and the fault detection process. This intermediary generates estimated signals that mediate the comparison with actual sensor readings, avoiding direct complex parameter estimation. The virtual model acts as a bridge that translates system behavior into comparable signals without requiring difficult parameter calculations.
2Reliability
If system parameters are estimated from sensor detections to detect multiplicative faults, then fault detection capability is improved, but the time and computational resources required increase
Solution Approach 1:
The patent pre-establishes a virtual model of the system that can generate estimated signals without requiring real-time complex parameter estimation. By having the virtual model ready and configured in advance, the system can perform fault detection by simply comparing current sensor readings against pre-computed or easily computed virtual model predictions, significantly reducing the time required for fault detection compared to real-time parameter estimation methods.
3Measurement precision
If multiple sensors are used in the system, then measurement accuracy is improved, but the difficulty in determining which specific sensor is faulty increases
Solution Approach 1:
The patent segments the fault detection process by creating individual virtual representations for each sensor within the virtual model. Each sensor's estimated signal can be independently compared with its corresponding actual reading, allowing the system to identify which specific sensor is faulty by detecting discrepancies in individual sensor channels rather than having to analyze the entire multi-sensor system collectively.
Data Source
AI summary
A method is described for determining multiplicative faults of a sensor installed in a system comprising a plurality of sensors, comprising the steps of: - detecting an effective target signal (s) from a target sensor, representative of a target quantity of the system; - detecting one or more auxiliary signals respectively from one or more auxiliary sensors of the system besides the target sensor, representative of auxiliary quantities of the system; - determining an estimated target signal (s*) representative of the target quantity from the one or more auxiliary signals; - determining a first quadratic difference (r+) between the effective target signal (s) multiplied by a multiplicative positive factor (c+) greater than 1, and the estimated target signal (s*); - determining a second quadratic difference (r) between the effective target signal (s) and estimated target signal (s*); - determining a third quadratic difference (r-) between the effective target signal (s) multiplied by a positive multiplicative factor (c-) smaller than 1, and the estimated target signal (s*); - determining a first ratio (r/r+) between the second (r) and first quadratic differences (r+); - determining a second ratio (r/r-) between the second (r) and third quadratic differences (r-); - comparing the first (r/r+) and second ratios (r/r-) with a first comparison factor (Kf); - determining the square of the effective target signal (s); - determining the square of the estimated target signal (s*); - comparing the square of the effective target signal (s) and square of estimated target signal (s*) with a second comparison factor (Ke); - establishing the presence of multiplicative faults of target sensor if at least one between the first (r/r+) and second ratios (r/r-) is greater than the first comparison factor (Kf), and at least one between the square of the effective target signal (s) and square of the estimated target signal (s*) is greater than said second comparison factor (Ke).