Laser-Directed Energy Deposition of H13: processing window and improved characterization procedures

Silvestri, Alessia Teresa; Bosetti, Paolo; Squillace, Antonino

doi:10.1080/10426914.2023.2219302

Cited by 2 publications

(1 citation statement)

References 41 publications

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“…Navigation grade systems guarantee the best performance based on fiber-optic sensors, which are bulky and expensive, but their value of typical errors (bias, drift, misalignment, and scale factor) is as low as to guarantee satisfactory inertial navigation, even without the need for further corrective work. The quality of IMU systems then decreases until they reach the other end of the scale, the consumer-grade systems, typically used for gaming or automotive applications [13][14][15][16]. Typically, these sensors are made of MEMS technology, which achieves significant improvements in size, weight, and cost [17].…”

Section: Introductionmentioning

confidence: 99%

The Use of Artificial Intelligence Approaches for Performance Improvement of Low-Cost Integrated Navigation Systems

Alteriis

Ruggiero

Prete

et al. 2023

Sensors

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In this paper, the authors investigate the possibility of applying artificial intelligence algorithms to the outputs of a low-cost Kalman filter-based navigation solution in order to achieve performance similar to that of high-end MEMS inertial sensors. To further improve the results of the prototype and simultaneously lighten filter requirements, different AI models are compared in this paper to determine their performance in terms of complexity and accuracy. By overcoming some known limitations (e.g., sensitivity on the dimension of input data from inertial sensors) and starting from Kalman filter applications (whose raw noise parameter estimates were obtained from a simple analysis of sensor specifications), such a solution presents an intermediate behavior compared to the current state of the art. It allows the exploitation of the power of AI models. Different Neural Network models have been taken into account and compared in terms of measurement accuracy and a number of model parameters; in particular, Dense, 1-Dimension Convolutional, and Long Short Term Memory Neural networks. As can be excepted, the higher the NN complexity, the higher the measurement accuracy; the models’ performance has been assessed by means of the root-mean-square error (RMSE) between the target and predicted values of all the navigation parameters.

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Section: Introductionmentioning

confidence: 99%

The Use of Artificial Intelligence Approaches for Performance Improvement of Low-Cost Integrated Navigation Systems

Alteriis

Ruggiero

Prete

et al. 2023

Sensors

View full text Add to dashboard Cite

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Effect of surface remelting on the characteristics of IN718 components fabricated using laser powder directed energy deposition

Thanumoorthy,

Jadhav,

Oyyaravelu

et al. 2024

Eng. Res. Express

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Laser Powder Directed Energy Deposition (LP-DED) fabricated components exhibit poor surface finish, necessitating additional post-processing steps prior to their practical application. Enhancing the surface quality of additively manufactured IN718 specimens through conventional post-processing methods is particularly challenging, given the material's poor machinability and the complexity of the fabricated components. The current study is centered on comprehending the impact of Laser Surface Remelting (LSR) on the surface properties of Laser Powder Directed Energy Deposited (LP-DED) IN718 material. To gain insights into how remelting influences surface characteristics, remelting was carried out using various sets of parameters. The remelted zone exhibited a refined grain structure, leading to increased hardness. Moreover, significant reductions in surface roughness and residual stress were observed in the remelted samples. Regression analysis indicated that laser power played a pivotal role, with positive impact on surface finish and depth of influence but a negative impact on residual stress and hardness. Therefore, considering all the comparison metrics, remelting using laser power of 150W and a scan speed of 1140mm/min were found to yield optimal surface conditions.

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Laser-Directed Energy Deposition of H13: processing window and improved characterization procedures

Cited by 2 publications

References 41 publications

The Use of Artificial Intelligence Approaches for Performance Improvement of Low-Cost Integrated Navigation Systems

The Use of Artificial Intelligence Approaches for Performance Improvement of Low-Cost Integrated Navigation Systems

Effect of surface remelting on the characteristics of IN718 components fabricated using laser powder directed energy deposition

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