The DICONDE information model for inspection of aircraft structures

Kurzfassung

Introduction: Non-destructive testing (NDT) ensures the reliability and integrity of aircraft structures by effective damage detection, localization and damage characterisation. NDT of aircraft structures involves a large amount of heterogeneous data associated with the inspection such as structure characteristics, flaw characterisation variables, NDT equipment parameters, settings, post-processing data and results. Acquired NDT data is a crucial asset. The heterogeneous and complex data needs proper integration and management to derive insights about the inspected structure. The DICONDE (Digital Imaging and Communication in Non-Destructive Evaluation) open standard is an important enabler for the storage, management and exchange of NDT data [1, 2, 3]. DICONDE is based on the Digital Imaging and Communications in Medicine (DICOM) standard [4]. However, the use of proprietary data formats, less documentation, software and isolated NDT systems introduce intricacies and challenges for data integration [5, 6]. This requires a standardized and structured approach to manage NDT data using DICONDE. Research Question: This research focuses on adopting the DICONDE information model for the inspection of components. The DICONDE information model defines a model to map the entities from the real world. With the structured representation of different types of NDT data generated by diverse inspection methods for a component under different states, the focus is on representing entity-relationships and properties of NDT data. Research Method: In this research, immersion ultrasonic testing (UT) data produced by a Hillger NDT system is used. Twelve composite samples at various states pre and post impact damage are inspected using UT through-transmission and pulse-echo methods. The UT system produces data in *.hgy format with the header data containing metadata such as inspection date and time, hardware configuration, probe information, coordinate information and resolution. A pydicom-based framework is developed to convert the proprietary data format into the DICONDE based *.dcm data format [6]. The DICONDE data model is defined using the DICONDE Information Object Definitions (IODs). IODs encapsulate information about real-world data. They are grouped together based on information entities (IE) about the NDT data which contain mandatory, conditional and optional metadata. Unique Identifiers (UIDs) used in the DICONDE standard ensure global uniqueness and thus information entities can be distinguished from one another. The condition of the composite samples at two different sessions are correlated using the entity-relationship diagram adopted from the DICOM standard (Figure 1). A composite sample, CAI 18 at the component level could include information such as an identifier (ID) or a name. All other data is organized based on this entity. Each component could have one or more Studies. In this case, the condition of the sample before impact and after impact are identified by Study Instance UIDs. Each Study has Series that represent inspections using the UT through-transmission method and the pulse-echo method. The Series UID is used to identify the series. Each Series might contain one or more Instances such as raw data, processed data (C-scans), equipment, equipment settings and annotations. Each instance is identified by a unique Service-Object Pair (SOP) Instance UID. Results and Conclusion: The DICONDE information model is suitable to handle NDT inspections from different time points and to store and manage the associated information. The relation between entities that are part of this inspection can be digitally mapped and stored using the DICONDE standard. The DICONDE open data standard is an important solution for the transition into NDE 4.0. Adopting the DICONDE open standard for NDT data formats ensures a structural approach for a robust database representation, seamless integration of data from heterogeneous NDT methods and data management across different inspection timelines for an aircraft structural component. Similarly, the completeness of NDT data enables the application of AI-based data analysis, which requires consistent data structures. The DICONDE information model addresses the critical needs for standardization, interoperability, data sharing, and integration of the NDT data for improving operational efficiency and decision-making in maintenance processes. A key challenge to overcome is the correct spatial alignment of data from different inspection systems. This is part of ongoing research and development. References: [1] ASTM E2339 E07.11 Committee, Standard Practice for Digital Imaging and Communication in Nondestructive Evaluation (DICONDE), West Conshohocken, PA: ASTM International, 2016. [2] ASTM E2663 E07.11 Committee, Standard Practice for Digital Imaging and Communication in Nondestructive Evaluation ({DICONDE}) for Ultrasonic Test Methods, West Conshohocken, PA: ASTM International, 2018. [3] N. Brierley, R. Casperson, D. Engert, S. Heilmann, F. Herold, D. Hofmann, H. Küchler, F. Leinenbach, S.-J. Lorenz, J. Martin, J. Rehbein, B. Sprau and A. Suppes, Specification ZfP 4.0 - 01E: DICONDE in Industrial Inspection, German Society for Non-Destructive Testing (DGZfP), 2023. [4] National Electrical Manufacturers Association (NEMA), Digital imaging and communications in medicine (DICOM), NEMA Standards Publications. [5] J. Aigner, H. Meyer, F. Raddatz and G. Wende, Digitalization of Repair Processes in Aviation: Process Mapping, Modelling and Analysis for Composite Structures., in Deutscher Luft- und Raumfahrtkongress 2023, Stuttgart, Germany, 2023. [6] G. Jacob and F. Raddatz, Data fusion for the efficient NDT of challenging aerospace structures: a review, in Proceedings Volume 12049, NDE 4.0, Predictive Maintenance, and Communication and Energy Systems in a Globally Networked World, Long Beach, California, United States, 2022. [7] Pydicom, Pydicom, [Online]. Available: https://pydicom.github.io/. [Accessed 12 January 2023]. [8] R. Casperson, Datenformate für die zerstörungsfreie Prüfung, BAM. [9] ASTM E3169 E07.11 Committee, Standard Guide for Digital Imaging and Communication in Nondestructive Evaluation ({DICONDE}), West Conshohocken, PA: ASTM International, 2018. [10] F. Leinenbach et al., Information reuse of nondestructive evaluation (NDE) data sets, Journal of Sensors and Sensor Systems, 2024. [11] OFFIS e.V. DICOM ToolKit (DCMTK); 2023. Available from: https://dicom.offis.de/de/dcmtk/.