Development of an optical system for geometric inspection of external surface of pipelines

2012 ◽  
Author(s):  
Maryah E. M. Haertel ◽  
Armando Albertazzi G. ◽  
João R. Melo ◽  
Maurício Reck ◽  
Darlan Becker ◽  
...  
Keyword(s):  
Optical System ◽  
External Surface ◽  
Geometric Inspection

scholarly journals SOLVING TRANSIENT INVERSE HEAT TRANSFER PROBLEMS IN COMPLEX GEOMETRIES USING PHYSICS-GUIDED NEURAL NETWORKS (PGNN)

2021 ◽  
Vol 2021 (3) ◽  
pp. 4540-4547
Author(s):  
D. Emonts ◽  
◽  
J. Yang ◽  
R. H. Schmitt ◽  
◽  
...  
Keyword(s):  
Heat Transfer ◽  
Heat Flow ◽  
Input Parameter ◽  
Temperature Fields ◽  
Elastic Behavior ◽  
Transient Temperature ◽  
Complex Geometries ◽  
Inverse Heat Transfer ◽  
Geometric Inspection ◽  
Transfer Problems

Temporally and spatially unstable thermal conditions lead to transient or inhomogeneous thermo-elastic behavior of workpieces during manufacturing or geometric inspection. Temperature monitoring by means of sensors consign transient temperature fields, but do not yield information about the heat flow acting as thermal boundary condition, which is a relevant input parameter for nearly any thermal simulation. Addressing the need for efficient methods, the authors propose an approach to solve inverse heat transfer problems in complex geometries. In the presented study, locally acting heat loads are experimentally investigated based on virtual demonstrators running in FEM. The conducted method shows high potential for transient heat flow modelling in terms of accuracy and computational efficiency.

Scale and Pose-Invariant Feature Quality Inspection for Freeform Geometries in Additive Manufacturing

2019 ◽  
Vol 141 (12) ◽  
Author(s):  
Yu Jin ◽  
Harry Pierson ◽  
Haitao Liao
Keyword(s):  
Additive Manufacturing ◽  
Point Cloud ◽  
Quality Inspection ◽  
Point Cloud Data ◽  
Inspection Method ◽  
Cloud Data ◽  
Geometric Dimensioning And Tolerancing ◽  
Geometric Inspection ◽  
3D Scanners ◽  
Feature Based

Abstract Additive manufacturing (AM) has the unprecedented ability to create customized, complex, and nonparametric geometry, and it has made this ability accessible to individuals outside of traditional production environments. Geometric inspection technology, however, has yet to adapt to take full advantage of AM’s abilities. Coordinate measuring machines are accurate, but they are also slow, expensive to operate, and inaccessible to many AM users. On the other hand, 3D-scanners provide fast, high-density measurements, but there is a lack of feature-based analysis techniques for point cloud data. There exists a need for developing fast, feature-based geometric inspection techniques that can be implemented by users without specialized training in inspection according to geometric dimensioning and tolerancing conventions. This research proposes a new scale- and pose-invariant quality inspection method based on a novel location-orientation-shape (LOS) distribution derived from point cloud data. The key technique of the new method is to describe the shape and pose of key features via kernel density estimation and detect nonconformities based on statistical divergence. Numerical examples are provided and tests on physical AM builds are conducted to validate the method. The results show that the proposed inspection scheme is able to identify form, position, and orientation defects. The results also demonstrate how datum features can be incorporated into point cloud inspection, that datum features can be complex, nonparametric surfaces, and how the specification of datums can be more intuitive and meaningful, particularly for users without special training.

scholarly journals Smartphone’s Sensing Capabilities for On-Board Railway Track Monitoring: Structural Performance and Geometrical Degradation Assessment

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
André Paixão ◽  
Eduardo Fortunato ◽  
Rui Calçada
Keyword(s):  
Low Cost ◽  
Railway Track ◽  
Structural Performance ◽  
Railway Infrastructure ◽  
Degradation Rates ◽  
Geometric Inspection ◽  
Recent Developments ◽  
Vertical Accelerations ◽  
Geometric Quality ◽  
Critical Situations

Railway infrastructure managers run dedicated inspection vehicles to monitor the geometric quality of the track (among other aspects) to detect irregularities and ensure safe running conditions of railway lines, in accordance with specific regulations. Unfortunately, these inspections disturb the normal traffic operation, especially in networks with intense traffic; are generally carried out only a few times per year; and, consequently, do not provide prompt identification of critical situations. Considering the recent developments and cost reduction in sensing capabilities of smartphones, the authors present an approach to use these technologies to perform constant acceleration measurements inside in-service trains to complement the assessment of the structural performance and geometrical degradation of the tracks. Cross-correlation values above 0.85 were obtained between the standard deviations of the longitudinal level and the experimental vertical accelerations measured on-board a passenger train on an 11-km railway stretch. The results showed that the approach can be used to identify critical situations that affect the performance of the track, regarding passenger comfort, degradation rates, and risk of derailment. It may comprise a low-cost and crowdsourced complement to the general current practice of track geometric inspection by dedicated vehicles and contribute to an earlier detection of track malfunctions, consequently, to a more efficient maintenance planning and infrastructure management.

Geometric Inspection in Surfboard Manufacturing by Using Reverse Engineering and 3D Inspection Tools

2021 ◽  
pp. 107-113
Author(s):  
Xabier Amezua ◽  
Eneko Solaberrieta ◽  
Xabier Garikano ◽  
Angel Perez ◽  
Florencio Fernandez ◽  
...  
Keyword(s):  
Reverse Engineering ◽  
Geometric Inspection
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