Using Sensor Data for the Development of Digital Twins in Support of Condition-Based Maintenance
Notice bibliographique
Résumé
This article examines how operational data obtained from sensors interacting with the Royal Canadian Navy (RCN) Halifax Class Frigates onboard Integrated Platform Management System (IPMS) could be used to support a shift from schedule-based maintenance to condition-based maintenance. The idea is to use a few years of IPMS data logged by the L3Harris Equipment Health Monitoring (EHM) software tool to aid in the development of EHM rules (or Digital Twins) that will indicate the current health status of various equipment. The process of EHM rules development consists of several steps. First, the targeted failure modes were selected by carrying out equipment failure modes and effects analysis (FMEA) and reviewing existing operational and maintenance records collected from the resource management system. For each targeted failure mode, relevant IPMS integrated sensors data was identified (when available), extracted, and checked for missing values, low signal to noise ratio and outliers. An equipment digital twin was created using L3Harris EHM built-in functions and/or Python programming language. Utilization of Python programming language functions allowed implementing EHM approach for wider range of equipment failure modes. Once the EHM rule was developed, it was tested using a different set of IPMS data. The results were analyzed and the digital twin model was reworked until a satisfactory response was confirmed. Numerous Digital twins (DTs) were created for critical equipment on board including propulsion diesel engine, drive train components, pumps, remotely controlled valves, and sensors. This development process demonstrated how sensors meant to support operational needs and benefit CBM. More value to be expected should the specific needs of CBM be considered early in the ship design. L3Harris IPMS was proven a valuable source of information to support the development of EHM rules necessary for CBM. In the course of this study, L3Harris DT engineering process was also validated by Lloyd’s Register and received “Digital Twin Ready Approval in Principle” certification. The performance of EHM rules still has to be validated in the field and its value to be confirmed by the end-users, but the work performed so far is promising.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».