Aligning PHM, SHM and CBM by understanding the physical system failure behaviour

In this work the three disciplines of condition based maintenance (CBM), structural health monitoring (SHM) and prognostics and health management (PHM) are described and the characteristics of the disciplines are compared. The three approaches are then demonstrated using three different case studies on bearing vibration monitoring, composite panel structural health monitoring and helicopter landing gear prognostics, respectively. After a discussion on the benefits of understanding the system (failure) behaviour, an integrated approach is proposed in\ud which the three disciplines are aligned. This approach starts from defining an appropriate monitoring strategy and eventually leads to decision support in taking the decisions that lead to an optimal maintenance process throughout the life cycle of the asset

Simulation based comparison of predictive maintenance policies

When an asset is operated in variable conditions, its operational efficiency can be improved significantly when the maintenance is performed in a dynamic manner. This means that variations in usage and operating environment are taken into account when deciding on the length of the maintenance intervals. Several predictive maintenance strategies, that enable such an approach, are nowadays being developed. However, demonstrating the benefits of these new maintenance concepts is generally difficult. As a result, implementation of the concepts is still rather limited. In this paper, a previously proposed modeling framework is used to quantify the performance of different maintenance policies for a navy frigate. A corrective policy will be used as a reference situation. Then the performance of a calendar time based, usage severity based and condition based maintenance policy will be calculated and compared to the reference policy. In all cases the performance of the policies is quantified through the total maintenance costs and the achieved system availability

Powder Characterization and Optimization for Additive Manufacturing

Achieving the optimal quality for Additive Manufactured (AM) parts does not only depend on setting the right process parameters. Material feedstock also plays an important role when aiming for high performance products. The metal AM processes that are most applicable to industry, Powder Bed Fusion and Directed Energy Deposition, use metal powder as raw material. Therefore, controlling the quality and correctly characterizing the particles used in the process is a key step to successfully apply metal AM techniques. A correct flow of the powder and a constant apparent density over the build plate/substrate ensure a smooth process, less porosity and better surface resolution. In the present paper a methodology for AM powder characterization will be proposed, based on parameters like particle size distribution and shape, and experimental results will be presented. A series of representative materials from the above-mentioned techniques are studied to find the optimal particle parameters required in the metal AM processes

Helicopter Rotor Blade Monitoring using Autonomous Wireless Sensor Network

The advancement on Wireless Sensor Networks for vibration monitoring presents important possibilities for helicopter rotor health and usage monitoring. While main rotor blades account for the main source of lift for helicopters, rotor induced vibration establishes an important source for understanding the rotor performance and blade condition. A discussion on the dual character of blades as rotating structures results in two different interrogation strategies for external and internal dynamic loading on the blade. The first strategy aims for in-flight rotor performance monitoring, while the second pursues health assessment. An overview of different measurements performed on an actual helicopter blade is presented. The measurements include a complete modal analysis using a full wired instrumented blade and a comparison between wireless sensor nodes and wired instrumentation. Additionally, a numerical multibody dynamics model for damage simulation is presented. The experimental and numerical work contribute to the identification of several implications on the migration of condition and health monitoring techniques to a wireless setting