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Diagnostic and Prognostic Metrics for Aerospace Propulsion Health Management Systems
- Aerospace Standard
- AIR7999
- Issued
Downloadable datasets available
Annotation ability available
Sector:
Issuing Committee:
Language:
English
Scope
This Aerospace Information Report (AIR) presents metrics for assessing the performance of diagnostic and prognostic algorithms and systems delivering propulsion health management functions.
Rationale
With the increasing application of diagnostic and prognostic technologies within the propulsion system community, there is a need for standardized metrics that can be used by developers and end users alike for assessing the performance of algorithms and systems for diagnosing faults and predicting the future health state of a system. The focus of this document is to introduce a variety of metrics that can be used for this purpose. Originally published in 2020, this document consolidates and expands upon the contents of two previous SAE E-32 Committee documents to create a single comprehensive document on diagnostic and prognostic metrics for Aerospace Propulsion Health Management Systems. The details of the other two documents are as follows:
With the publication of this document, the two superseded documents, AIR4985 and AIR5909, will be cancelled. This document consolidation strategy was agreed to by the SAE E-32 Committee to reduce the number of documents it is required to maintain.
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Topic
Data Sets - Support Documents
| Title | Description | Download |
|---|---|---|
| Unnamed Dataset 1 | ||
| Unnamed Dataset 2 | ||
| Unnamed Dataset 3 | ||
| Unnamed Dataset 4 | ||
| Table 1 | Distribution in nominal and faulted engines | |
| Table 2 | ProDiMES sensed output parameters | |
| Table 3 | ROC AUC and AAC results | |
| Table 4 | TPR, TNR, FPR, and FNR detection metric results | |
| Table 5 | Fault detection metrics for WSSR fault detection method | |
| Table 6 | Fault detection metrics for 3 point median WSSR fault detection method | |
| Table 7 | CIR and kappa coefficient metric results | |
| Table 8 | Fault isolation metrics for WLS isolation with WSSR detection | |
| Table 9 | Fault isolation metrics for WLS isolation with median WSSR detection | |
| Table 10 | Fault isolation metrics for PNN isolation with WSSR detection | |
| Table 11 | Fault isolation metrics for PNN isolation with median WSSR detection | |
| Table 12 | Average bias, MAE, MAPE, and sample standard deviation results | |
| Table 13 | Estimated RUL results | |
| Table 14 | α-λ accuracy results | |
| Table 15 | RA and CRA results | |
| Unnamed Dataset 20 | ||
| Unnamed Dataset 21 | ||
| Unnamed Dataset 22 |
Issuing Committee
E-32 Aerospace Propulsion Systems Health Management
Background
Engine condition monitoring and rotorcraft HUMS(Health and Usage Monitoring Systems)can be used as a tool to track and restore engine performance, improve problem diagnosis, suggest solutions, promote better commercial and military aircraft operation, minimize in-flight failures, and reduce costs of engine maintenance. Because of these and other continuing objectives, the need for consolidated action by a group of experts to promote engine monitoring and rotorcraft condition monitoring know-how and standards was identified. It was deemed appropriate by the SAE Propulsion Division to assign this task to a special committee designated as Committee E-32. The committee has existed for over 40 years and has 26 active members. Purpose / Charter E-32 Committee serves as a forum to gather, record, and publish expert information in the discipline of aerospace propulsion system health management. The Committee gathers and analyzes requirements for propulsion system health management for the various types of air vehicle propulsion systems and develops standards and recommendations for the adoption of aerospace propulsion system health management devices that affect the operation of propulsion systems. Objectives Identifies potential propulsion system parameters suitable for sensing (pressure, temperature, vibration, etc.) and considerations involved in selecting parameters (potential problems, accuracy, cost, etc.), Analyzes the various approaches to aerospace propulsion system health management (e.g., airborne vibration health management systems, fault prediction capabilities, ground software interfaces, etc.) and establishes criteria for cost effective systems, and guidance regarding best practices for designing propulsion health management systems, Develops appropriate standards for aerospace propulsion system health management equipment and techniques; e.g., types of sensors, identification of signals which should be led to common diagnostic connectors, etc., Develops new requirements and uses for aerospace propulsion system health management to promote sustainable and cost effective operation of air vehicles, and Hosts technical conferences related to health management of propulsion systems. Provide a means to gain regulatory approval for utilizing EHM data in a range of maintenance activities.Reference
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