scholarly journals Investigation of the Algorithm to Find Defects in High-voltage Insulators for an Automated Thermal Imaging Control System

2021 ◽  
Vol 288 ◽  
pp. 01070
Author(s):  
Alina Zaripova ◽  
Damir Zaripov ◽  
Alexander Usachev
Keyword(s):  
High Voltage ◽  
Defect Detection ◽  
Thermal Imaging ◽  
Laboratory Tests ◽  
Subjective Assessment ◽  
Brightness Distribution ◽  
Joint Analysis ◽  
Infrared Images ◽  
Standard Value ◽  
The Mean

This paper describes a software algorithm for detecting defective insulating structures using infrared images. The defect detection criteria are based on a joint analysis of the mean and standard value of the brightness distribution of a set of insulators. The effectiveness of the developed criteria is substantiated by the results of laboratory tests of a significant number of insulators removed from high-voltage lines according to the results of thermal imaging diagnostics. Simultaneous analysis of thermograms of the same type of insulating structures according to the proposed algorithm is more effective in comparison with the subjective assessment of each of them separately, which was used earlier. In addition, this approach allows to reduce the time of analysis and decision-making based on the results of diagnostics.

Platelet Suruival and Function in Rats with Enhanced Thrombotic Tendency

1985 ◽  
Vol 54 (04) ◽  
pp. 739-743 ◽  
Author(s):  
Federica Delaini ◽  
Elisabetta Dejana ◽  
Ine Reyers ◽  
Elisa Vicenzi ◽  
Germana De Bellis Vitti ◽  
...  
Keyword(s):  
Arachidonic Acid ◽  
Nephrotic Syndrome ◽  
Platelet Function ◽  
Laboratory Tests ◽  
Thrombus Formation ◽  
The Other ◽  
Mean Survival Time ◽  
The Mean ◽  
And Function ◽  
Thrombotic Tendency

SummaryWe have investigated the relevance of some laboratory tests of platelet function in predicting conditions of thrombotic tendency. For this purpose, we studied platelet survival, platelet aggregation in response to different stimuli, TxB2 and 6-keto-PGFlα production in serum of rats bearing a nephrotic syndrome induced by adriamycin. These animals show a heavy predisposition to the development of both arterial and venous thrombosis. The mean survival time was normal in nephrotic rats in comparison to controls. As to aggregation tests, a lower aggregating response was found in ADR-treated rats using ADP or collagen as stimulating agents. With arachidonic acid (AA) we observed similar aggregating responses at lower A A concentrations, whereas at higher AA concentrations a significantly lower response was found in nephrotic rats, despite their higher TxB2 production. Also TxB2 and 6-keto-PGFlα levels in serum of nephrotic rats were significantly higher than in controls. No consistent differences were found in PGI2-activity generated by vessels of control or nephrotic rats.These data show that platelet function may appear normal or even impaired in rats with a markedly increased thrombotic tendency. On the other hand, the significance of high TxB2 levels in connection with mechanisms leading to thrombus formation remains a controversial issue.

Ocular surface temperature differences in glaucoma

2021 ◽  
pp. 112067212110237
Author(s):  
Ari Leshno ◽  
Ori Stern ◽  
Yaniv Barkana ◽  
Noa Kapelushnik ◽  
Reut Singer ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Thermal Imaging ◽  
Ocular Surface ◽  
Open Angle Glaucoma ◽  
Tissue Temperature ◽  
Body Temperatures ◽  
Current Thinking ◽  
Imaging Camera ◽  
The Mean ◽  
The Difference

Purpose: Accumulating evidence suggests that neuroinflammation and immune response are part of the sequence of pathological events leading to optic nerve damage in glaucoma. Changes in tissue temperature due to inflammation can be measured by thermographic imaging. We investigated the ocular surface temperature (OST) profile of glaucomatous eyes to better understand the pathophysiology of these conditions. Methods: Subjects diagnosed with glaucoma (primary open angle glaucoma [POAG] or pseudo exfoliation glaucoma [PXFG]) treated at the Sam Rothberg Glaucoma Center (11/2019–11/2020.) were recruited. Healthy subjects with no ocular disease served as controls. The Therm-App thermal imaging camera was used for OST acquisition. Room and body temperatures were recorded, and the mean temperatures of the medial cantus, lateral cantus, and cornea were calculated with image processing software. Results: Thermographic images were obtained from 52 subjects (52 eyes: 25 POAG and 27 PXFG) and 66 controls (66 eyes). Eyes with glaucoma had a significantly higher OST compared to controls (mean 0.9 ± 0.3°C, p < 0.005). The difference between the two groups remained significant after adjustment for age, sex, intraocular pressure (IOP) and room and body temperatures. Lens status and topical IOP-lowering medication did not significantly affect OST. A subgroup analysis revealed that the OST was higher among eyes with POAG compared to eyes with PXFG, but not significantly. Conclusions: Differences in the OST between glaucomatous and normal eyes strengthens current thinking that inflammation affects the pathophysiology of glaucoma. Longitudinal studies are warranted to establish the prognostic value of thermographic evaluations in these patients.

Lightweight detection algorithm for fine-grained surface defects of aerospace seal rings

2021 ◽  
pp. 1-18
Author(s):  
Hui Liu ◽  
Boxia He ◽  
Yong He ◽  
Xiaotian Tao
Keyword(s):  
Feature Extraction ◽  
Defect Detection ◽  
Surface Defect ◽  
Surface Defects ◽  
Detection Algorithm ◽  
Seal Ring ◽  
Fine Grained ◽  
Aerospace Applications ◽  
Surface Defect Detection ◽  
The Mean

The existing seal ring surface defect detection methods for aerospace applications have the problems of low detection efficiency, strong specificity, large fine-grained classification errors, and unstable detection results. Considering these problems, a fine-grained seal ring surface defect detection algorithm for aerospace applications is proposed. Based on analysis of the stacking process of standard convolution, heat maps of original pixels in the receptive field participating in the convolution operation are quantified and generated. According to the generated heat map, the feature extraction optimization method of convolution combinations with different dilation rates is proposed, and an efficient convolution feature extraction network containing three kinds of dilated convolutions is designed. Combined with the O-ring surface defect features, a multiscale defect detection network is designed. Before the head of multiscale classification and position regression, feature fusion tree modules are added to ensure the reuse and compression of the responsive features of different receptive fields on the same scale feature maps. Experimental results show that on the O-rings-3000 testing dataset, the mean condition accuracy of the proposed algorithm reaches 95.10% for 5 types of surface defects of aerospace O-rings. Compared with RefineDet, the mean condition accuracy of the proposed algorithm is only reduced by 1.79%, while the parameters and FLOPs are reduced by 35.29% and 64.90%, respectively. Moreover, the proposed algorithm has good adaptability to image blur and light changes caused by the cutting of imaging hardware, thus saving the cost.

scholarly journals Image Enhanced Mask R-CNN: A Deep Learning Pipeline with New Evaluation Measures for Wind Turbine Blade Defect Detection and Classification

2021 ◽  
Vol 7 (3) ◽  
pp. 46
Author(s):  
Jiajun Zhang ◽  
Georgina Cosma ◽  
Jason Watkins
Keyword(s):  
Deep Learning ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Defect Detection ◽  
Recognition Rate ◽  
Weighted Average ◽  
Wind Turbine Blade ◽  
Evaluation Measures ◽  
Augmentation Techniques ◽  
The Mean

Demand for wind power has grown, and this has increased wind turbine blade (WTB) inspections and defect repairs. This paper empirically investigates the performance of state-of-the-art deep learning algorithms, namely, YOLOv3, YOLOv4, and Mask R-CNN for detecting and classifying defects by type. The paper proposes new performance evaluation measures suitable for defect detection tasks, and these are: Prediction Box Accuracy, Recognition Rate, and False Label Rate. Experiments were carried out using a dataset, provided by the industrial partner, that contains images from WTB inspections. Three variations of the dataset were constructed using different image augmentation settings. Results of the experiments revealed that on average, across all proposed evaluation measures, Mask R-CNN outperformed all other algorithms when transformation-based augmentations (i.e., rotation and flipping) were applied. In particular, when using the best dataset, the mean Weighted Average (mWA) values (i.e., mWA is the average of the proposed measures) achieved were: Mask R-CNN: 86.74%, YOLOv3: 70.08%, and YOLOv4: 78.28%. The paper also proposes a new defect detection pipeline, called Image Enhanced Mask R-CNN (IE Mask R-CNN), that includes the best combination of image enhancement and augmentation techniques for pre-processing the dataset, and a Mask R-CNN model tuned for the task of WTB defect detection and classification.

scholarly journals Salvage Arthrodesis with Femoral Head Allograft for Failed Total Ankle Arthroplasty

2020 ◽  
Vol 5 (4) ◽  
pp. 2473011420S0032
Author(s):  
Hong S. Lee ◽  
Kiwon Young ◽  
Tae-Hoon Park ◽  
Hong Seop Lee
Keyword(s):  
Femoral Head ◽  
Subjective Assessment ◽  
Total Ankle Arthroplasty ◽  
Bone Block ◽  
Ankle Arthroplasty ◽  
Pain Scores ◽  
Walking Aids ◽  
The Mean ◽  
Final Followup

Category: Ankle Introduction/Purpose: Failed total ankle arthroplasty (TAA) often results in significant bone loss and requires salvage arthrodesis. The aim of this study was to investigate the outcomes of Salvage arthrodesis with allo-bone block for failed TAA. Methods: This study included 8 patients who underwent salvage arthrodesis with femoral head allograft for failed TAA from August 2012 to March 2018 because of loosing of TAA implant. The mean age of the patients was 71 years (range, 54-81 years), and the mean follow-up period was 32 months (range, 12 to 84 months). Allograft problem and alignment of joint were evaluated radiographically. American Orthopaedic Foot & Ankle Society (AOFAS) scores, Foot and Ankle Outcome Score (FAOS), and visual analogue scale (VAS) pain scores were recorded preoperatively and at the time of final followup. Functional questionnaires were used to assess the duration for which the patient could walk continuously, use of walking aids, consumption of pain medication, and the patient’s subjective assessment of the percentage of overall improvement compared with before the salvage arthrodesis. Results: The allograft was retained without collapse for a mean of 24 months (range, 12 to 36 months) in four patients. Collapse of the allograft was observed in four patients at a mean of 11 months (range, 9 to 16 months), 1 of 4 patients were conserved to retrograde intramedullary nail at postoperative 12 months because of with implant failure and nonunion. The mean AOFAS and VAS pain scores improved from 12 (range, 8 to 40) preoperatively to 63 (range, 38 to 75) postoperatively (p = 0.001) and from 7 (range, 6 to 10 to 3 (range, 2 to 8) (p = 0.001), respectively. At the final follow-up evaluation, 6 of 8 patients were able to walk continuously at least 30 minutes with walking aid. Conclusion: The successful rate of salvage arthrodesis with femoral head allograft was 75% (Six of total 8 patients). The incidence rate of allograft collapse was 50% (Four of total 8 patients).

scholarly journals The epidemiology and influence of osteoarthritis on clinical, laboratory and ultrasound parameters of patients with early rheumatoid arthritis

2019 ◽  
Vol 2 (1) ◽  
pp. 41-47
Author(s):  
Teodora Serban ◽  
Iulia Satulu ◽  
Ioana Cretu ◽  
Oana Vutcanu ◽  
Mihaela Milicescu ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Disease Activity ◽  
Laboratory Tests ◽  
Clinical Laboratory ◽  
Early Arthritis ◽  
Symptom Duration ◽  
Knee Oa ◽  
The Mean ◽  
Clear Predominance ◽  
Ultrasound Parameters

AbstractBackground: Osteoarthritis (OA) and rheumatoid arthritis (RA) can overlap and the presence of OA can interfere with the evaluation of patients with RA.Objectives: The aim of this study was to evaluate the possible impact of OA on the clinical, laboratory and ultrasound parameters currently evaluated in patients with early RA (ERA).Methods: We have evaluated the data obtained from patients with ERA referred to our Early Arthritis Research Center (EARC). Only data from patients who fulfilled EULAR/ ACR 2010 criteria for RA and had symptom duration of less than 12 months were analyzed. All patients underwent clinical examination, laboratory tests and ultrasound (US) examination.Results: There was a clear predominance of women (62.8%). The mean age was 55.47±13.71 years. At baseline, 21 patients (48.8%) were diagnosed with OA. Hand OA did not influence the values of any of the parameters assessed (p>0.05). For patients with knee OA, significantly higher values were observed only for DAS28 at baseline (p=0.018) as well as after 12 months of observation (p=0.031).Conclusions: Significantly higher values of DAS28 were observed in patients with ERA who associated knee OA, while the values of SDAI were not influenced, suggesting that SDAI may be superior to DAS28 in evaluating patients with ERA and knee OA. The values of patient’s VAS were not influenced by the presence of hand or knee OA suggesting that these types of OA do not influence the patients’ perception of the disease activity. Moreover, the values of ultrasound scores were not influenced by the presence of OA.

scholarly journals Application of Zernike moments in computer vision problems for infrared images

2021 ◽  
Vol 310 ◽  
pp. 01002
Author(s):  
Dmitriy Otkupman ◽  
Sergey Bezdidko ◽  
Victoria Ostashenkova
Keyword(s):  
Computer Vision ◽  
Machine Vision ◽  
Thermal Imaging ◽  
Imaging System ◽  
Infrared Region ◽  
Zernike Moments ◽  
Infrared Images ◽  
Theoretical Justification ◽  
Thermal Imaging System ◽  
Binarization Method

The efficiency of using Zernike moments when working with digital images obtained in the infrared region of the spectrum is considered to improve the accuracy and speed of an autonomous thermal imaging system. The theoretical justification of the choice of Zernike moments for solving computer (machine) vision problems and the choice of a suitable threshold binarization method is given. In order to verify the adequacy and expediency of using the chosen method, practical studies were conducted on the use of Zernike methods for distorting various thermal images in shades of gray.

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