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This study aims to solve the problems of ambiguous localization, large calculation, poor real-time and limited applicability of bolt thread defect detection.

First, the acquired ultrasound image is used to acquire the larger area of the image, which is set as the compliant threaded area. Second, based on the determined coordinates of the center point in each selected region, the set of coordinates on the left and right sides of the bolts is acquired by DBSCAN method with parameters eps and MinPts, which is determined by data set dimension D and the k-distance curve. Finally, the defect detection boundary line fitting is completed using the acquired coordinate set, and the relationship between the distance from each detection point to the curve and d, which is obtained from the measurement of the standard bolt sample with known thread defect, is used to locate the bolt thread defect simultaneously.

In this paper, the bolt thread defect detection method with ultrasonic image is proposed; meanwhile, the ultrasonic image acquisition system is designed to complete the real-time localization of bolt thread defects.

The detection results show that the method can effectively detect bolt thread defects and locate the bolt thread defect location with wide applicability, small calculation and good real-time performance.

Simulations exist for the prediction of the behaviour of building structural systems under fire, including two-way coupled fire-structure interaction. However, these simulations do not include detailed models of the connections, whereas these connections may impact the overall behaviour of the structure. Therefore, this paper proposes a two-scale method to include screw connections.

The two-scale method consists of (a) a global-scale model that models the overall structural system and (b) a small-scale model to describe a screw connection. Components in the global-scale model are connected by a spring element instead of a modelled screw, and the stiffness of this spring element is predicted by the small-scale model, updated at each load step. For computational efficiency, the small-scale model uses a proprietary technique to model the behaviour of the threads, verified by simulations that model the complete thread geometry, and validated by existing pull-out experiments. For four screw failure modes, load-deformation behaviour and failure predictions of the two-scale method are verified by a detailed system model. Additionally, the two-scale method is validated for a combined load case by existing experiments, and demonstrated for different temperatures. Finally, the two-scale method is illustrated as part of a two-way coupled fire-structure simulation.

It was shown that proprietary ”threaded connection interaction” can predict thread relevant failure modes, i.e. thread failure, shank tension failure, and pull-out. For bearing, shear, tension, and pull-out failure, load-deformation behaviour and failure predictions of the two-scale method correspond with the detailed system model and Eurocode predictions. Related to combined load cases, for a variety of experiments a good correlation has been found between experimental and simulation results, however, pull-out simulations were shown to be inconsistent.

More research is needed before the two-scale method can be used under all conditions. This relates to the failure criteria for pull-out, combined load cases, and temperature loads.

The two-scale method bridges the existing very detailed small-scale screw models with present global-scale structural models, that in the best case only use springs. It shows to be insightful, for it contains a functional separation of scales, revealing their relationships, and it is computationally efficient as it allows for distributed computing. Furthermore, local small-scale non-convergence (e.g. a screw failing) can be handled without convergence problems in the global-scale structural model.

Simulating the behavior of clothing has always been of interest in the apparel, fashion and computer game industries. With the development of these industries, there is a need to increase the accuracy of clothing simulation techniques. A garment contains many seams whose behavior affects its final appearance. In this study, a numerical model is presented to simulate seam puckers in single- and double-layer fabrics.

A yarn-level simulation technique has been used for this purpose. Based on this technique, the individual threads in the fabric structure and the sewing threads are modeled separately. Then, their behavior and interaction with each other are considered in the seam pucker model.

The model is used to simulate the real samples. The results show that the proposed model is able to simulate the degree of seam puckering for a single-layer fabric with an average error of 7.9% and for a double-layer fabric with an average error of 8.5%.

The behavior of the seam is affected by the properties, behavior and interaction of the sewing threads and yarns in the fabric structure. In previous studies, the parameters related to seams and fabrics were not fully considered. In this study, a new yarn-level model is presented to simulate seam puckering in woven fabrics. The most important advantage of this type of simulation is the ability to examine the interaction of fabric threads as well as the interaction of sewing threads with each other and with the threads of the fabric structure.

Through this research study, the authors found that digital thread has made significant progress in the life cycle management of the US Air Force. The authors hope that by reviewing similar studies in the aerospace field, the meaning of digital thread can be summarized and applied to a wider range of fields. In addition, theoretically, the definition of digital twin and digital thread are not unified. The authors hope that the comparison of digital thread and digital twin will better enable scholars to distinguish between the two concepts. Besides, the authors are also looking forward that more people will realize the significance of digital thread and carry out future research.

Complete research about digital thread and the relevant concept of the digital twin is conducted. First, by searching in Google Scholar with the keyword “digital thread”, the authors filter results and save literature with high relevance to digital thread. The authors also track these papers’ references for more paper of digital thread and digital twin. After removing the duplicate and low-relevance literature, 72 digital thread-related literature studies are saved and further analyzed from the perspective of time development, application field and research directions.

Digital thread application in industries other than the aviation manufacturing industry is still relatively few, and the research on the application of digital thread in real industrial scenarios is mainly at the stage of framework design and design-side decision optimization. In addition, the digital thread needs a new management mechanism and organizational structure to realize landing. The new management mechanism and the process can adapt to the whole life cycle management process based on the digital thread, manage the data security and data update, and promote the digital thread to play a better effect on the organizational management.

Based on a review of digital thread, future research directions and usage suggestions are given. The fault diagnosis of high-speed train bogie as an example shows the effectiveness of the method and also partially demonstrates the advantages and effects brought by the digital thread connecting the data models at various stages.

This paper first investigates and analyzes the theoretical connotation and research progress of digital thread and gives a complete definition of digital thread from the perspective of the combination of digital thread and digital twins. Next, the research process of digital thread is reviewed, and the application fields, research directions and achievements in recent years are summarized. Finally, taking the fault diagnosis of high-speed train bogie as an example partially demonstrates the advantages and effects brought by the digital thread connecting the data models at various stages.

The purpose of this review paper is to define the dominating factors (such as fiber, yarn, fabric structure, sewing thread, sewing needle and machine parameters) that affect the seam damages and causing defects. It also describes the various explanations of sewing defects in garment production and critically analyzes them for optimum selection of parameters and speeds for minimizing such faults. Hence, the knowledge of various factors which affect the sewing damages/defects will be helpful for garment manufacturers/researchers to know influence of the parameters and control the quality of producing seam.

This section is not applicable for a review paper.

Sewing damages such as needle cut and other sewing damages/defects are studied mostly in woven fabric. There are very few studies conducted on knitted fabric sewing damages/defects. The sewing damage problems do not have single solution that is capable of removing these damages in fabric. All the determined and affecting parameters related to fiber, yarn, fabric construction, sewing thread and sewing machine must be examined to design appropriate remedial measurement related to machine design, fabric parameters and sewing thread. This could help in minimizing or eliminating the needle cut and other sewing damage problems.

It is an original review work and is helpful for garment manufacturers/researchers to reduce the defects and be able to produce good quality seam.

This paper aims to propose the artificial neural network (ANN) and regression models for the estimation of the thread consumption at multilayered seam assembly stitched with lock stitch 301.

In the present study, the generalized regression and neural network models are developed by considering the fabric types: woven, nonwoven and multilayer combination thereof, with basic sewing parameters: sewing thread linear density, stitch density, needle count and fabric assembly thickness. The network with feed-forward backpropagation is considered to build the ANN, and the training function trainlm of MATLAB software is used to adjust weight and basic values according to the optimization of Levenberg Marquardt. The performance of networks measured in terms of the mean squared error and the layer output is set according to the sigmoid transfer function.

The proposed ANN and regression model are able to predict the thread consumption with more accuracy for multilayered seam assembly. The predictability of thread consumption from available geometrical models, regression models and industrial empirical techniques are compared with proposed linear regression, quadratic regression and neural network models. The proposed quadratic regression model showed a good correlation with practical thread consumption value and more accuracy in prediction with an overall 4.3% error, as compared to other techniques for given multilayer substrates. Further, the developed ANN network showed good accuracy in the prediction of thread consumption.

The estimation of thread consumed while stitching is the prerequisite of the garment industry for inventory management especially with the introduction of the costly high-performance sewing thread. In practice, different types of fabrics are stitched at multilayer combinations at different locations of the stitched product. The ANN and regression models are developed for multilayered seam assembly of woven and nonwoven fabric blend composition for better prediction of thread consumption.

The purpose of this paper is to make performance improvements and timely critical execution enhancements for operational flight program (OFP). The OFP is core software of autonomous control system of small unmanned helicopter.

In order to meet the time constraints and enhance control application performance, two major improvements were done at real‐time operating system (RTOS) kernel. They are thread scheduling algorithm and lock‐free thread message communication mechanism. Both of them have a direct relationship with system efficiency and indirect relationship with helicopter control application execution stability through improved deadline keeping characteristics.

In this paper, the suitability of earliest deadline first (EDF) scheduling algorithm and non‐blocking buffer (NBB) mechanism are illustrated with experimental and practical applications. Results of this work show that EDF contributes around 15 per cent finer‐timely execution and NBB enhances kernel's responsiveness around 35 per cent with respect to the number of thread context switch and CPU utilization. These apply for OFP implemented over embedded configurable operating system (eCos) RTOS on x86 architecture‐based board.

This paper illustrates an applicability of deadline‐based real‐time scheduling algorithm and lock‐free kernel communication mechanism for performance enhancement and timely critical execution of autonomous unmanned aerial vehicle control system.

This paper illustrates a novel approach to extend RTOS kernel modules based on unmanned aerial vehicle control application execution scenario. Lock‐free thread communication mechanism is implemented, and tested for applicability at RTOS. Relationship between UAV physical and computation modules are clearly illustrated via an appropriate unified modelling language (UML) collaboration and state diagrams. As experimental tests are conducted not only for a particular application, but also for various producer/consumer scenarios, these adequately demonstrate the applicability of extended kernel modules for general use.

The purpose of this paper is to mathematically model the structure of doubled fancy yarns made by combining together several threads.

It was assumed that such a structure may have two distinctive parts – sinusoidal and helical (i.e. sigmoidal). This model is based on calculating the length of the effect thread in relation to the core thread. The case of having several variants of such a structure was discussed to account for several types of doubled fancy yarns. The number of wraps of the binder, the overfed ratio, and heights of the fancy profiles in the different parts were the fundamental parameters of this model. The effects of changes in the number of wraps, the overfeed ratio or both simultaneously, on this model, were also considered. The shape factor of fancy yarn was also modelled depending on the basic model of the structure.

The model was tested and the correlation coefficient between the theoretical value and the real value of length of the effect thread was 0.90.

This model is useful for predicting the length of the effect component based on the type, dimension and number of the fancy profiles of doubled fancy yarn, and for understanding the changes of the multiple-thread structure of fancy yarn when the overfeed ratio and/or the number of wraps were to change.

Studies the effect of thread tension and the stitch length, L, as well as the fabric thickness, t, and its compressive modulus, E, on the seam balance and total thread consumption.

Knitted fabrics have been widely used in a wide range of applications such as apparel industry. Since these fabrics are continuously subjected to the long-term tensile stresses or tensile creep in real conditions, investigation of viscoelastic behavior of sewn knitted fabrics would be important especially at the seamed area. The paper aims to discuss this issue.

A lockstitch machine was used to produce sewn samples by knitted fabric. Factors such as stitch per inch (SPI), thread tension and thread type were variables of the model. Tensile creep tests under constant load of 200 N were conducted, and creep compliance parameter D(t) of samples was obtained as a response variable. A successive residual method (SRM) was also used to characterize viscoelastic properties of sewn-seamed fabrics.

The instantaneous elastic responses of the seamed samples were less than those of the neat fabric (fabric with no seam). An increase in sewing thread strength increases the instantaneous elastic response of the sample. SPI and thread tension have an optimum value to increase E₀. High tenacity polyester thread, due to its higher elastic modulus, caused a larger E₀ than polyester/cotton thread in sewn knitted fabric. Characteristics of seam including sewing thread type, SPI and sewing tension have significant influence on T₀. Sewn-seamed fabric by high modulus thread shows less viscous strain T₀ than the neat fabric (fabric with no seam). Viscous strain T₀ decreases as SPI changes from 8 to 4 and/or 12. SPI and thread tension have an optimum value to increase the viscous strain T₀. E1 is the same for optimum seamed fabric and fabric sample but T1 is about two times greater for seamed fabric. Retarded time for creep recovery increases by sewing process but characteristics of seam have significant influence on E1 and T1. All sewn knitted fabric samples used in this study could be described by Burger’s model, which is a Maxwell model paralleled with a Kelvin one.

This paper is going to use a different method named successive residuals to model the creep behavior of seamed knitted fabric. On the whole, this paper paved a way to obtain viscoelastic constants of sewn-seamed knitted fabrics based on different sewing parameters such as the modulus of elasticity of the sewing thread, SPI and sewing thread tension.