|
1
|
Ma M, Cao H, Jiang M, Sun L, Zhang L, Zhang F, Sui Q, Tian A, Liang J, Jia L. High Precision Detection Method for Delamination Defects in Carbon Fiber Composite Laminates Based on Ultrasonic Technique and Signal Correlation Algorithm. MATERIALS 2020; 13:ma13173840. [PMID: 32878129 PMCID: PMC7503374 DOI: 10.3390/ma13173840] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 08/08/2020] [Accepted: 08/24/2020] [Indexed: 12/02/2022]
Abstract
This paper presents a method based on signal correlation to detect delamination defects of widely used carbon fiber reinforced plastic with high precision and a convenient process. The objective of it consists in distinguishing defect and non-defect signals and presenting the depth and size of defects by image. A necessary reference signal is generated from the non-defect area by using autocorrelation theory firstly. Through the correlation calculation results, the defect signal and non-defect signal are distinguished by using Euclidean distance. In order to get more accurate time-of-flight, cubic spline interpolation is introduced. In practical automatic ultrasonic A-scan signal processing, signal correlation provide a new way to avoid problems such as signal peak tracking and complex gate setting. Finally, the detection results of a carbon fiber laminate with artificial delamination through ultrasonic phased array C-scan acquired from Olympus OmniScan MX2 and this proposed algorithm are compared, which showing that this proposed algorithm performs well in defect shape presentation and location calculation. The experiment shows that the defect size error is less than 4%, the depth error less than 3%. Compared with ultrasonic C-scan method, this proposed method needs less inspector’s prior-knowledge, which can lead to advantages in automatic ultrasonic testing.
Collapse
Affiliation(s)
- Mengyuan Ma
- School of Control Science and Engineering, Shandong University, Ji’nan 250061, China; (M.M.); (H.C.); (L.Z.); (F.Z.); (Q.S.); (L.J.)
| | - Hongyi Cao
- School of Control Science and Engineering, Shandong University, Ji’nan 250061, China; (M.M.); (H.C.); (L.Z.); (F.Z.); (Q.S.); (L.J.)
| | - Mingshun Jiang
- School of Control Science and Engineering, Shandong University, Ji’nan 250061, China; (M.M.); (H.C.); (L.Z.); (F.Z.); (Q.S.); (L.J.)
- Correspondence:
| | - Lin Sun
- Zhongche Qingdao Sifang Locomotive and Rolling Stock Co., Ltd, Qingdao 266111, China; (L.S.); (A.T.); (J.L.)
| | - Lei Zhang
- School of Control Science and Engineering, Shandong University, Ji’nan 250061, China; (M.M.); (H.C.); (L.Z.); (F.Z.); (Q.S.); (L.J.)
| | - Faye Zhang
- School of Control Science and Engineering, Shandong University, Ji’nan 250061, China; (M.M.); (H.C.); (L.Z.); (F.Z.); (Q.S.); (L.J.)
| | - Qingmei Sui
- School of Control Science and Engineering, Shandong University, Ji’nan 250061, China; (M.M.); (H.C.); (L.Z.); (F.Z.); (Q.S.); (L.J.)
| | - Aiqin Tian
- Zhongche Qingdao Sifang Locomotive and Rolling Stock Co., Ltd, Qingdao 266111, China; (L.S.); (A.T.); (J.L.)
| | - Jianying Liang
- Zhongche Qingdao Sifang Locomotive and Rolling Stock Co., Ltd, Qingdao 266111, China; (L.S.); (A.T.); (J.L.)
| | - Lei Jia
- School of Control Science and Engineering, Shandong University, Ji’nan 250061, China; (M.M.); (H.C.); (L.Z.); (F.Z.); (Q.S.); (L.J.)
| |
Collapse
|