Advances in Dynamic Foundation Testing Technology

2009 ◽  
Author(s):  
Garland Likins ◽  
Ingemar Hermansson ◽  
Mike Kightley ◽  
Jon Cannon ◽  
David Klingberg
Keyword(s):  
Testing Technology

Softsensorgestützte Oberflächenkonditionierung beim Außenlängsdrehen 42CrMo4/Development of a reference force model for soft sensor supported surface conditioning during longitudinal turning of AISI 4140 QT

2020 ◽  
Vol 110 (11-12) ◽  
pp. 758-762
Author(s):  
Daniel Gauder ◽  
Michael Biehler ◽  
Benedict Stampfer ◽  
Benjamin Häfner ◽  
Volker Schulze ◽  
...  
Keyword(s):  
White Layer ◽  
Surface States ◽  
Soft Sensor ◽  
Sensor Technology ◽  
Force Model ◽  
Destructive Testing ◽  
Surface Conditioning ◽  
Testing Technology ◽  
Process Detection ◽  
Longitudinal Turning

Das Forschungsprojekt „Prozessintegrierte Softsensorik zur Oberflächenkonditionierung beim Außenlängsdrehen von 42CrMo4“ widmet sich der Entstehung und der In-process-Erfassung von industriell relevanten Randschichtzuständen. Im Speziellen werden sogenannte White Layer und Eigenspannungszustände untersucht. Durch die modulare Verknüpfung von zerstörungsfreier Prüftechnik, Simulationsergebnissen und Prozesswissen mittels Datenfusion wird ein Softsensor erforscht. Dieser soll im Rahmen einer adaptiven Regelung des Drehprozesses eingesetzt werden und eine gezielte Einstellung von vorteilhaften Randschichtzuständen erlauben. The research project „Process-integrated soft sensor technology for surface conditioning during external longitudinal turning of 42CrMo4“ is dedicated to the formation and in-process-detection of surface layers with industrial relevance. In particular, so-called white layers and residual stresses are investigated. A soft sensor is being researched through the modular combination of non-destructive testing technology and process knowledge by means of data fusion. This is to be used in the context of an adaptive control of the turning process in order to adjust beneficial surface states.

scholarly journals Research on road engineering detection method based on GPR technology

2020 ◽  
Vol 165 ◽  
pp. 04014
Author(s):  
Liu Tao ◽  
Li Jia ◽  
Zheng Zhi-gang ◽  
Huang Zhi ◽  
Jiang Jian ◽  
...  
Keyword(s):  
Parameter Setting ◽  
Non Destructive Testing ◽  
Practical Application ◽  
Distribution Law ◽  
Destructive Testing ◽  
Road Engineering ◽  
The Road ◽  
Image Optimization ◽  
Testing Technology ◽  
Non Destructive

GPR is an effective non-destructive testing technology. This paper introduces its composition principle and operation method, explains the process of parameter setting and image optimization, obtains the dielectric constant of 10000 points, compares it with the density, and then obtains the uniformity distribution law of construction quality based on image. By calibrating the thickness of the road surface, the effective detection of road diseases can be realized, and the theoretical basis and practical application conditions of GPR technology can be clarified.

Study on the Glass Beads Refractive Index Testing Technology

2012 ◽  
Vol 487 ◽  
pp. 805-809
Author(s):  
Jun Ma ◽  
Dong Hua Guo
Keyword(s):  
Refractive Index ◽  
Glass Bead ◽  
Glass Beads ◽  
Research Trend ◽  
Future Research ◽  
The Future ◽  
Testing Technology ◽  
At Home

this thesis discusses the main testing technologies at home and abroad relating to the glass bead refractive index, analyses the research emphases relating to the glass bead refractive index testing technology at present and point out the future research trend.

scholarly journals THink: Inferring Cognitive Status from Subtle Behaviors

AI Magazine ◽  
2015 ◽  
Vol 36 (3) ◽  
pp. 49-60 ◽  
Author(s):  
Randall Davis ◽  
David Libon ◽  
Roda Au ◽  
David Pitman ◽  
Dana Penney
Keyword(s):  
Neuropsychological Testing ◽  
Cognitive Status ◽  
Major Advance ◽  
Test Results ◽  
Clock Drawing Test ◽  
The Past ◽  
Drawing Test ◽  
Testing Technology ◽  
Opening Up

The digital clock drawing test is a fielded application that provides a major advance over existing neuropsychological testing technology. It captures and analyzes high precision information about both outcome and process, opening up the possibility of detecting subtle cognitive impairment even when test results appear superficially normal. We describe the design and development of the test, document the role of AI in its capabilities, and report on its use over the past seven years. We outline its potential implications for earlier detection and treatment of neurological disorders. We set the work in the larger context of the THink project, which is exploring multiple approaches to determining cognitive status through the detection and analysis of subtle behaviors.

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