2020
DOI: 10.3390/met10020169
|View full text |Cite
|
Sign up to set email alerts
|

A Fast Identification Method of Yield Strength of Materials Based on Bending Experimental Data

Abstract: Identifying the yield strength of materials quickly and accurately is the key to realizing defect prediction and digital process control on the production line. This paper focuses on identifying the material yield strength based on bending deformation, analyzing the influence of different die fillets, punch fillets, and die spans on the curve shapes, determining the reasonable dimensions of the device, and developing them. Two methods for rapidly extracting the yield load are proposed—the window vector method … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2021
2021
2022
2022

Publication Types

Select...
2

Relationship

1
1

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 35 publications
0
1
0
Order By: Relevance
“…The data points before yield bending are used to optimize the elastic modulus, and the transition points between elastic and plastic bending are used to optimize the yield strength, while the data points after yield bending are used to optimize the hardening parameters, and the unloading data points are used to optimize the variable modulus parameters. The window method [32] is used to automatically identify the (14)…”
Section: Sequential Identification Strategy For Nominal Parametersmentioning
confidence: 99%
“…The data points before yield bending are used to optimize the elastic modulus, and the transition points between elastic and plastic bending are used to optimize the yield strength, while the data points after yield bending are used to optimize the hardening parameters, and the unloading data points are used to optimize the variable modulus parameters. The window method [32] is used to automatically identify the (14)…”
Section: Sequential Identification Strategy For Nominal Parametersmentioning
confidence: 99%