Closed-Loop Fault Detection via Tracking Error Frequency Filtering
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Solution Overview
Problem
Modern diesel engines face challenges in detecting faults in closed-loop systems, such as EGR systems, which can lead to NOx and particulate matter emission exceedances due to restrictions, leaks, or faulty sensors/actuators, requiring precise high-fidelity flow measurement and monitoring to maintain compliance with stringent emissions regulations.
Innovation Solution
A system and method for monitoring closed-loop systems that involve filtering tracking error signals to isolate frequency components impacted by faults, generating an accumulated error signal, and comparing it with a predetermined threshold to detect off-nominal behavior and raise alerts, utilizing a combination of filter modules and fault processing logic to identify system faults.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional fault detection methods are used in closed-loop systems, then the system structure remains simple, but fault detection accuracy is insufficient leading to false alarms or missed detections
Solution Approach 1:
The monitoring system segments the tracking error signal into different frequency components using filter modules. Each filter isolates specific frequency bands that are characteristic of different fault types, allowing the system to analyze multiple aspects of system behavior simultaneously without requiring a single complex detection algorithm
Solution Approach 2:
The system transforms the one-dimensional tracking error signal into a multi-dimensional analysis by examining multiple frequency components across different bands. This dimensional transformation allows fault detection to occur in the frequency domain rather than just the time domain, improving detection accuracy while using standard signal processing techniques
2Reliability
If high-fidelity flow measurement is implemented to detect faults, then emission compliance is improved, but system cost and complexity increase
Solution Approach 1:
The system continuously monitors the tracking error signal from the closed-loop control system and feeds this information back through filter modules and accumulators. This feedback mechanism allows the system to detect faults based on deviations from expected behavior without requiring additional measurement hardware, maintaining emission compliance reliability while avoiding increased system complexity
Solution Approach 2:
The monitoring system utilizes existing control system signals (tracking error) to perform fault detection, rather than requiring separate measurement systems. The closed-loop control system's own error signals are repurposed for diagnostic functions, allowing the system to self-monitor its health without external intervention or additional expensive sensors
3Speed
If continuous monitoring of tracking error is performed without filtering, then response time is fast, but noise interference increases causing false alarms
Solution Approach 1:
The continuous tracking error signal is segmented into distinct frequency bands using filter modules. Each band captures specific types of fault-related information while excluding noise in other frequency ranges. This segmentation allows the system to maintain continuous monitoring (fast response) while reducing noise interference through selective frequency analysis
Solution Approach 2:
The system employs periodic filtering and accumulation operations at defined sampling intervals. The filter modules process the tracking error signal at regular intervals, and accumulators integrate the filtered signals over predetermined periods. This periodic processing maintains fast detection response while the integration over time reduces the impact of random noise fluctuations
Data Source
AI summary
A closed-loop system having a controllable variable is monitored to detect the off-nominal behavior and raise an alert when fault is detected. The faults show up in such a way that the tracking error signal is impacted and this impact manifests itself as a change in the frequency components. A filter isolates a band of frequency components of the tracking error signal that are more impacted than others by deviation caused by a fault to be detected. The filter can effectively amplify the section of the error tracking signal that contains the frequency components having impact. In addition, the filter will also have the characteristics to attenuate the impact of other frequency components. An accumulated error signal is generated from the filtered tracking error signal, compared with a predetermined fault threshold characteristic, and a fault alert is provided if a predetermined threshold is satisfied.