Online Inspection for Glass Fiber Forming

2006 ◽  
Vol 129 (1) ◽  
pp. 164-171 ◽  
Author(s):  
Paul P. Lin ◽  
Qing Guo ◽  
Xiaolong Li
Keyword(s):  
Glass Fiber ◽  
Fiber Diameter ◽  
Glass Melting ◽  
Noise Removal ◽  
Video Signals ◽  
Pixel Location ◽  
Inspection Process ◽  
Trained Neural Network ◽  
Online Inspection

Glass fiber forming is a complicated process in which many factors could affect the quality of fibers. The forming machine has many fiber-forming tubes that are close to each other and arranged in several layers. The closeness results in inadequate lighting and unwanted video signals. An anti-causal zero-phase filter was employed to remove noise with insignificant pixel location shift or distortion. In addition to the noise, the unwanted video signals constantly moving from one place to another also presented a challenge in image analysis. These signals were identified by a trained neural network that classified patterns. The unwanted signal identification through instant pattern classification made online inspection possible. During the fiber drawing process, the diameters of glass forming tubes and the profiles of glass melting cones were closely monitored and measured online in order to control the final fiber diameter. The accurate diameter measurements were accomplished by the noise removal along with a subpixel-resolution based edge detection technique. The results thus obtained for noise removal and unwanted video signals identification were quite good. The fiber diameter measurements were performed online, and the entire inspection process was automated with the aid of a programmable logic controller.

An improved nonlinear model considering relative velocity for the friction behavior between untwisted glass-fiber tow and roller

2021 ◽  
pp. 004051752110308
Author(s):  
Yang Liu ◽  
Zhong Xiang ◽  
Xiangqin Zhou ◽  
Zhenyu Wu ◽  
Xudong Hu
Keyword(s):  
Friction Coefficient ◽  
Glass Fiber ◽  
Relative Velocity ◽  
Friction Model ◽  
Woven Fabric ◽  
Test Results ◽  
Application Process ◽  
Friction Behavior ◽  
Improved Model

Friction between the tow and tool surface normally happens during the tow production, fabric weaving, and application process and has an important influence on the quality of the woven fabric. Based on this fact, this paper studied the influence of tension and relative velocity on the three kinds of untwisted-glass-fiber tow-on-roller friction with a Capstan-based test setup. Furthermore, an improved nonlinear friction model taking both tension and velocity into account was proposed. According to statistical test results, firstly, the friction coefficient was found to be positively correlated with tension and relative velocity. Secondly, tension and velocity were complementary on the tow-on-roller friction behavior, with neither being superior to the other. Thirdly, an improved model was found to present well the nonlinear characteristics between friction coefficient and tension and velocity, and predicational results of the model were found to agree well with the observations from Capstan tests.

scholarly journals AMPLIFIER DESIGN FOR MODELING THE TRANSMISSION OF A DIGITAL VIDEO SIGNAL OVER A DATA TRANSMISSION CHANNEL

2021 ◽  
Vol 445 (1) ◽  
pp. 39-45
Author(s):  
M. Amreev ◽  
R. Safin ◽  
T. Pavlova ◽  
E. Temyrkanova ◽  
Y. Garmashova
Keyword(s):  
Transmission Line ◽  
Video Surveillance ◽  
Video Transmission ◽  
Main Task ◽  
Surveillance Systems ◽  
Video Signals ◽  
Ohmic Resistance ◽  
In Series ◽  
Amplifier Design

The use of video surveillance systems is used in the areas of security, law and order, in the territories of protected objects, in monitoring the movement of road vehicles and in other areas. The main disadvantage of a video surveillance system is its susceptibility to weather influences (rain, fog, snowfall, etc.), which degrades the quality of the video system by reducing the signal level. Therefore, the urgency of finding new ways and possibilities to improve the quality of video signals is one of the priority areas of signal processing. The main task of this work was to determine the main parameters, simulate the transmission line and amplifier, and select the schematic diagram of the transmitting and receiving path with the voltage and current ratings. Both the receiver and the cable video transmitter have different means of adjusting to different transmission line lengths. The signal at the output of each receiver should be in the range from 0.9 to 1.1 V, and the spread of the total ohmic resistance of the wires of the video transmission line at the input of the receiver should be no more than 2 – 3%. Based on these parameters, the equipment is configured for transmitting video over the channel. The magnitude of the mismatch is regulated by potentiometers, which allow smooth adjustment of the video transmission equipment [1]. As a rule, video transmission over the channel is carried out at a distance of 50 to 1500 m. If it is necessary to transmit video at distances less than 50 m, additional resistances are connected in series at the receiver input so that the total line resistance is 30 - 50 Ohm [1].

scholarly journals Analysis of the surface quality of polycaprolactam 3D prints enriched with carbon and glass fiber

2021 ◽  
Vol 338 ◽  
pp. 01005
Author(s):  
Damian Dzienniak ◽  
Jan Pawlik
Keyword(s):  
Glass Fiber ◽  
Surface Quality ◽  
Fused Deposition Modeling ◽  
Polyamide 6 ◽  
Fiber Glass ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
The Impact ◽  
The Relationship

Additive manufacturing has been gaining popularity and availability year by year, which has resulted in its dynamic development. The most common 3D printing method as of today, FDM (Fused Deposition Modeling), owing to its peculiarity, does not always guarantee producing objects with low surface roughness. The authors of the present article have taken on the analysis of the impact of FDM printing on the roughness of the filament thus processed. They also investigate the relationship between the roughness of the unprocessed filament (made of polycaprolactam, that is, polyamide 6 or PA6) with admixtures of other materials (carbon fiber, glass fiber) and the surface quality of the manufactured object. The main subject of the analysis is the side surfaces of 3D prints, as it is their quality that is usually directly dependent on many factors connected with the process of the laying of the consecutive layers. The authors check step by step whether there exists a pronounced relationship between the roughness of the original filament material and the roughness of the obtained surface.

scholarly journals Massive computational acceleration by using neural networks to emulate mechanism-based biological models

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Shangying Wang ◽  
Kai Fan ◽  
Nan Luo ◽  
Yangxiaolu Cao ◽  
Feilun Wu ◽  
...  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Mechanistic Model ◽  
Time Frame ◽  
Biological Applications ◽  
Biological Models ◽  
Parametric Space ◽  
Trained Neural Network ◽  
Short Time

Abstract For many biological applications, exploration of the massive parametric space of a mechanism-based model can impose a prohibitive computational demand. To overcome this limitation, we present a framework to improve computational efficiency by orders of magnitude. The key concept is to train a neural network using a limited number of simulations generated by a mechanistic model. This number is small enough such that the simulations can be completed in a short time frame but large enough to enable reliable training. The trained neural network can then be used to explore a much larger parametric space. We demonstrate this notion by training neural networks to predict pattern formation and stochastic gene expression. We further demonstrate that using an ensemble of neural networks enables the self-contained evaluation of the quality of each prediction. Our work can be a platform for fast parametric space screening of biological models with user defined objectives.

scholarly journals Physico-Mechanical Properties of the Poly(oxymethylene) Composites Reinforced with Glass Fibers under Dynamical Loading

Polymers ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2064 ◽  
Author(s):  
Stanisław Kuciel ◽  
Patrycja Bazan ◽  
Aneta Liber-Kneć ◽  
Aneta Gądek-Moszczak
Keyword(s):  
Mechanical Properties ◽  
Glass Fiber ◽  
Fiber Diameter ◽  
Glass Fibers ◽  
Fiber Reinforced Composites ◽  
Dynamic Loads ◽  
Fatigue Properties ◽  
Reinforced Composites ◽  
The Impact ◽  
Microscopy Images

The paper evaluated the possibility of potential reinforcing of poly(oxymethylene) (POM) by glass fiber and the influence of fiberglass addition on mechanical properties under dynamic load. Four types of composites with glass fiber and another four with carbon fiber were produced. The fiber content ranged from 5% to 40% by weight. In the experimental part, the basic mechanical and fatigue properties of POM-based composites were determined. The impact of water absorption was also investigated. The influence of fiber geometry on the mechanical behavior of fiber-reinforced composites of various diameters was determined. To refer to the effects of reinforcement and determine the features of the structure scanning electron microscopy images were taken. The results showed that the addition of up to 10 wt %. fiberglass increases the tensile properties and impact strength more than twice, the ability to absorb energy also increases in relation to neat poly(oxymethylene). Fiber geometry also has a significant impact on the mechanical properties. The study of the mechanical properties at dynamic loads over time suggests that composites filled with a smaller fiber diameter have better fatigue properties.

scholarly journals body2vec: 3D Point Cloud Reconstruction for Precise Anthropometry with Handheld Devices

2020 ◽  
Vol 6 (9) ◽  
pp. 94
Author(s):  
Magda Alexandra Trujillo-Jiménez ◽  
Pablo Navarro ◽  
Bruno Pazos ◽  
Leonardo Morales ◽  
Virginia Ramallo ◽  
...  
Keyword(s):  
Network Architecture ◽  
Point Cloud ◽  
Point Clouds ◽  
Noise Removal ◽  
Extraction Methods ◽  
Anthropometric Measurements ◽  
Handheld Devices ◽  
Background Removal ◽  
3D Point Cloud Reconstruction

Current point cloud extraction methods based on photogrammetry generate large amounts of spurious detections that hamper useful 3D mesh reconstructions or, even worse, the possibility of adequate measurements. Moreover, noise removal methods for point clouds are complex, slow and incapable to cope with semantic noise. In this work, we present body2vec, a model-based body segmentation tool that uses a specifically trained Neural Network architecture. Body2vec is capable to perform human body point cloud reconstruction from videos taken on hand-held devices (smartphones or tablets), achieving high quality anthropometric measurements. The main contribution of the proposed workflow is to perform a background removal step, thus avoiding the spurious points generation that is usual in photogrammetric reconstruction. A group of 60 persons were taped with a smartphone, and the corresponding point clouds were obtained automatically with standard photogrammetric methods. We used as a 3D silver standard the clean meshes obtained at the same time with LiDAR sensors post-processed and noise-filtered by expert anthropological biologists. Finally, we used as gold standard anthropometric measurements of the waist and hip of the same people, taken by expert anthropometrists. Applying our method to the raw videos significantly enhanced the quality of the results of the point cloud as compared with the LiDAR-based mesh, and of the anthropometric measurements as compared with the actual hip and waist perimeter measured by the anthropometrists. In both contexts, the resulting quality of body2vec is equivalent to the LiDAR reconstruction.

De-noising of transient electromagnetic data based on the long short-term memory-autoencoder

2020 ◽  
Vol 224 (1) ◽  
pp. 669-681
Author(s):  
Sihong Wu ◽  
Qinghua Huang ◽  
Li Zhao
Keyword(s):  
Field Data ◽  
Short Term Memory ◽  
Noise Removal ◽  
Data Sets ◽  
Late Time ◽  
Short Term ◽  
Term Memory ◽  
Transient Electromagnetic ◽  
Long Short Term Memory

SUMMARY Late-time transient electromagnetic (TEM) data contain deep subsurface information and are important for resolving deeper electrical structures. However, due to their relatively small signal amplitudes, TEM responses later in time are often dominated by ambient noises. Therefore, noise removal is critical to the application of TEM data in imaging electrical structures at depth. De-noising techniques for TEM data have been developed rapidly in recent years. Although strong efforts have been made to improving the quality of the TEM responses, it is still a challenge to effectively extract the signals due to unpredictable and irregular noises. In this study, we develop a new type of neural network architecture by combining the long short-term memory (LSTM) network with the autoencoder structure to suppress noise in TEM signals. The resulting LSTM-autoencoders yield excellent performance on synthetic data sets including horizontal components of the electric field and vertical component of the magnetic field generated by different sources such as dipole, loop and grounded line sources. The relative errors between the de-noised data sets and the corresponding noise-free transients are below 1% for most of the sampling points. Notable improvement in the resistivity structure inversion result is achieved using the TEM data de-noised by the LSTM-autoencoder in comparison with several widely-used neural networks, especially for later-arriving signals that are important for constraining deeper structures. We demonstrate the effectiveness and general applicability of the LSTM-autoencoder by de-noising experiments using synthetic 1-D and 3-D TEM signals as well as field data sets. The field data from a fixed loop survey using multiple receivers are greatly improved after de-noising by the LSTM-autoencoder, resulting in more consistent inversion models with significantly increased exploration depth. The LSTM-autoencoder is capable of enhancing the quality of the TEM signals at later times, which enables us to better resolve deeper electrical structures.

scholarly journals Improve inspection process in tire manufacturing by using computer simulation

2018 ◽  
Vol 192 ◽  
pp. 01048
Author(s):  
Sathitthep Sangthong ◽  
Pattara Woraphu ◽  
Kanokbhorn Arayikanon
Keyword(s):  
Working Condition ◽  
Production Capacity ◽  
Plant Production ◽  
Quality Inspection ◽  
Test Procedures ◽  
Average Production ◽  
Engineering And Technology ◽  
Inspection Process ◽  
Working Groups

The purity of this research was to study the feasibility of improving the quality inspection in the manufacturing of tire by focusing on the utilization process. The current plant production is continuous and there are four working groups which can be divided into 3 shifts with 24 hours produced a day (Average production capacity is 350 days per year). Improved quality inspection processes will inevitably result in unnecessary production stops. Therefore, the researchers have proposed a feasibility study on how to improve the quality of the test procedures using engineering and technology techniques. These create models that have the same functionality as the current working condition. The result was found that Model 2 could reduce unnecessary processes and also four workers per shift if the worker's wage was calculated. This model shows a cost reduction of approximately 1.68 million baht per year, as well as utilization process

scholarly journals Evaluation of Grinding of Unfilled and Glass Fiber Reinforced Polyamide 6,6

Polymers ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2288
Author(s):  
Roberto Spina ◽  
Bruno Cavalcante
Keyword(s):  
Surface Roughness ◽  
Glass Fiber ◽  
Grinding Wheel ◽  
Grinding Process ◽  
Fiber Reinforced ◽  
Liquid Coolant ◽  
Part Quality ◽  
Glass Fiber Reinforced ◽  
Process Trends

This paper investigates the grinding process on unreinforced (PA66) and reinforced glass-fiber polyamide 6,6 (PA66 GF30) with Al2O3 and SiC abrasive wheels. Both materials were ground by varying rotations, workpiece infeed speed, depth of cuts for sequential roughing/finishing steps. Dry and liquid coolant conditions were also considered during the grinding process to evaluate the effects on part quality. The surface roughness was used to assess the quality of the final products with several parameter combinations, identifying the induced process trends. The results show that at the end of the finishing step, the surface roughness Rz was lower than 4 μm, attaining the lowest value of 1.34 μm for PA66 specimens. The analysis also suggested the choice of the Al2O3 grinding wheel to reach the lowest Rz values for both materials.

Thermal Properties of Vacuum Insulation Panels with Glass Fiber

2012 ◽  
Vol 446-449 ◽  
pp. 3753-3756 ◽  
Author(s):  
Wang Ping Wu ◽  
Zhao Feng Chen ◽  
Jie Ming Zhou ◽  
Xue Yu Cheng
Keyword(s):  
Thermal Conductivity ◽  
Glass Fiber ◽  
Fiber Diameter ◽  
Core Material ◽  
The Core ◽  
Vacuum Insulation ◽  
Getter Effect ◽  
Porosity Ratio ◽  
Home Appliance ◽  
Heat Flow Meter

The VIPs consist of the glass-fiber core material and two types of envelope film. The glass fiber was fabricated by a centrifugal blowing process. The core material was prepared by the wet method. The thermal conductivities of the core material and VIPs were measured by the heat flow meter. The thermal conductivity for six pieces of 1mm thick core material is less than that for one piece of 6mm thick core material, which is affected by the fiber diameter, porosity ratio and the largest pore size diameter. The VIP for the building material has a low thermal conductivity (<0.008W/mK). The VIP for the home appliance has a lower thermal conductivity (<0.003W/mK). The VIP maintains a high-uniform thermal conductivity values due to the getter effect.

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