Joint Scanning Laser Thermography Defect Detection Method for Carbon Fiber Reinforced Polymer

He, Ziming; Wang, Hongjin; He, Yunze; Zhang, Guixiang; Wang, Jiazheng; Zou, Gaoyu; Chady, Tomasz

doi:10.1109/jsen.2019.2941077

Cited by 45 publications

(13 citation statements)

References 30 publications

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“…Particularly, with self-learning, adaptive and self-organizing characteristics, the BP-ANN model is very suitable for recognition of patterns in complex systems and has a strong ability to deal with nonlinear problems [23][24][25][26]. Considering the correlation between the input variables, principal component analysis (PCA) was used for dimension reduction before BP-ANN modelling [27]. e normal BP-ANN model generally consists of an input layer, a hidden layer and an output layer as functional processing units.…”

Section: Data Modellingmentioning

confidence: 99%

Development and Validation of a Photoplethysmography System for Noninvasive Monitoring of Hemoglobin Concentration

Liu

Peng

et al. 2020

Journal of Electrical and Computer Engineering

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Background. Traditional invasive hemoglobin (Hb) detection led to delayed diagnosis, operational inefficiency, incorrect critical decision making, and uncomfortable patient experience. To facilitate real-time total hemoglobin (tHb) monitoring, a portable prototype of a noninvasive Hb detection system was developed, and the accuracy of Hb predicted based on partial least squares (PLS) as well as backpropagation artificial neural network (BP-ANN) models was validated. Results. The prototype was combined with a signal processing circuit and a spectrophotometric probe containing 8 wavelength LEDs light source and photodiode array. Laboratory invasive Hb (Lab_tHb) and spot check Hb measurements with PLS (SpHb_PLS) and BP (SpHb_BP) methods were obtained simultaneously by hematology analyzer and the designed system. The invasive and noninvasive estimates of the Hb levels were analyzed using Spearman correlation as well as Bland–Altman plot and receiver operating characteristic (ROC) curve analysis. A total of 238 volunteers had attempted laboratory invasive and noninvasive spot check Hb measurements. Mean Lab_tHb, SpHb_PLS, and SpHb_BP were 13.6 ± 1.80 g/dL, 13.5 ± 1.07 g/dL, and 13.6 ± 1.06 g/dL, respectively. Noninvasive SpHb_PLS (r = 0.61, p<0.001) and SpHb_BP (r = 0.62, p<0.001) had a strong correlation with invasive tHb values. The Bland–Altman plot showed excellent consistency between the proposed noninvasive methods and laboratory invasive reference. In ROC analysis, PLS and BP models were good at predicting Hb ≥ 12 g/dL with area under the curve of 0.828 and 0.824, respectively. Observed differences between invasive and noninvasive Hb measurements displayed no significant correlation with perfusion index values. Conclusions. The result confirmed that noninvasive Hb monitoring had an excellent correlation with traditional invasive Hb measurement. Furthermore, it is suggested that the developed prototype has the potential for the noninvasive detection of Hb concentration with the methods of PLS and BP-ANN.

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Section: Data Modellingmentioning

confidence: 99%

Development and Validation of a Photoplethysmography System for Noninvasive Monitoring of Hemoglobin Concentration

Liu

Peng

et al. 2020

Journal of Electrical and Computer Engineering

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“…Optical measuring devices involve binocular vision, holographic interferometry, and laser triangulation. The laser triangulation method is widely applied for accurate measurement because of its high measurement accuracy, small size device, and fast measurement speed [6][7][8]. So, the laser scanning detection was applied to our system to obtain the outer contour data of the expansion joints of bellows.…”

Section: Detection Principlementioning

confidence: 99%

“…The fitted straight line equation can be expressed as Equation (8), where a is the intercept and b is the slope. z c = a + bx c (8) In order to get the convolution pitch value, the point cloud data need to be coordinate-transformed. The coordinate transformation consists of two basic transformations.…”

Section: Coordinate Transformationmentioning

confidence: 99%

Detection System for U-Shaped Bellows Convolution Pitches Based on a Laser Line Scanner

Yang

Chen

Liu

et al. 2020

Sensors

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An expansion joint is mainly composed of bellows and other components; it is attached on a container shell or pipe to compensate for the additional stress caused by temperature differences and mechanical vibrations. In China, the expansion joint fatigue tests are often used to assess the quality of products. After fatigue tests, convolution pitch will be changed. The amount of change is an important index that can be used to evaluate bellows expansion joints. However, the convolution pitch detection is mainly done manually and randomly by inspection agencies before shipping to the end users. This common practice is not efficient and is often subjective. This paper introduced a novel method for automatically detecting the change of the convolution pitch based on a laser line scanner and data processing technology. The laser line scanner is combined with a precision motorized stage to obtain the point cloud data of the bellows. After denoising and fitting, a peak-finding algorithm is applied to search for the crest of a convolution. The method to find the convolution pitch and the decision that needs to be made to ensure product eligibility are described in detail. A DN500 expansion joint is used as a sample to illustrate the efficiency of the system. The application of the technique intuitively allows a higher precision and relative efficiency in quality inspection of bellows expansion joints. It has also been implemented in the Special Equipment Safety Supervision and Inspection Institute of Jiangsu province with great success.

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“…The proposed approach gives the benefit of enhanced detection area along with enhanced defect detection efficiency. In [21], the authors proposed a joint scanning laser thermography approach to detect flat bottom holes in carbon fiber reinforced polymer. A scanning scheme along with the reconstruction approach is proposed to increase the defect detection efficiency of the existing state-of-the-art thermographic post-processing algorithms.…”

Section: Introductionmentioning

confidence: 99%

“…Online a-Step: compute { , ,Ν} by (21) configurations can be found in [43]. In our experimental study a movable IT excitation source is used for the scanning of the specimen.…”

mentioning

confidence: 99%

Sparse Low-Rank Tensor Decomposition for Metal Defect Detection Using Thermographic Imaging Diagnostics

Ahmed

Gao

Woo

2021

IEEE Trans. Ind. Inf.

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Joint Scanning Laser Thermography Defect Detection Method for Carbon Fiber Reinforced Polymer

Cited by 45 publications

References 30 publications

Development and Validation of a Photoplethysmography System for Noninvasive Monitoring of Hemoglobin Concentration

Development and Validation of a Photoplethysmography System for Noninvasive Monitoring of Hemoglobin Concentration

Detection System for U-Shaped Bellows Convolution Pitches Based on a Laser Line Scanner

Sparse Low-Rank Tensor Decomposition for Metal Defect Detection Using Thermographic Imaging Diagnostics

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