Piezoresistive carbon nanotube (CNT) sensors have garnered significant attention in structural health monitoring due to their exceptional sensitivity and design flexibility. Most CNT sensors, particularly those domina...
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Piezoresistive carbon nanotube (CNT) sensors have garnered significant attention in structural health monitoring due to their exceptional sensitivity and design flexibility. Most CNT sensors, particularly those dominated by the tunneling effect, exhibit a nonlinear resistance-strain response under uniaxial tension, where the evolution of the conductive network follows a distinct staged pattern, typically categorized into a gradual increase stage, a rapid increase stage, and a breakdown stage. However, existing studies often oversimplify the resistance-strain relationship, either omitting segmentation entirely or relying on subjectively determined inflection points, which limits the practical utilization of these features. In this study, an inflection point identification algorithm was developed based on the cumulative growth rate, which automatically extracts the transition inflection point between the first two stages and assigns its corresponding strain as the pre-warning strain threshold. This approach has the potential to meet the demand for early warning in structural health monitoring. Experimental validation was conducted using CNT/thermoplastic polyurethane (TPU) sensors fabricated through a coating process, confirming the algorithm's reliability and the reproducibility of the inflection phenomenon. The results indicated that the strain warning threshold of the fabricated sensors falls within the range of 0.44–1.14%, aligning well with the initial damage strain range of carbon fiber-reinforced polymer (CFRP) structures, facilitating the detection of matrix cracking, fiber breakage, and interlayer delamination. Furthermore, by adjusting the coating thickness and CNT content, the tunability of the inflection point position was revealed, leading to an initial parameter design guideline that provides flexible solutions for diverse engineering applications.
The image trees described hierarchically organise image segments according to scale, with the coarsest scale, the scale of the image itself as the root of the tree and the finest scales as the leaves. The segmentation...
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The image trees described hierarchically organise image segments according to scale, with the coarsest scale, the scale of the image itself as the root of the tree and the finest scales as the leaves. The segmentation algorithm used to form the tree nodes is the sieve, a nonlinear morphological scale-space operator. The trees are a transform, so it is possible to reconstruct the associated image without loss. Scale trees may have more nodes than are needed but the trees may be simplified using a standard statistical test to reduce the number of nodes without affecting the reconstructed image significantly. These simplified trees may be used to generate regions for a stereo algorithm that reduces the errors in the resulting disparity map, particularly within sharp-edged regions with low texture - conditions where conventional methods often fail.
In this paper we propose a novel technique of using a hybrid evolutionary;method, which uses a combination of genetic algorithm and matrix based solution methods such, as QR factorization. The training of the model is...
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In this paper we propose a novel technique of using a hybrid evolutionary;method, which uses a combination of genetic algorithm and matrix based solution methods such, as QR factorization. The training of the model is based on a layer based hierarchical structure for the architecture and the weights for the Artificial Neural Network classifier. The architecture for the classifier is found using a binary search type procedure. The hierarchical structured algorithm (EALS-BT) is also a hybrid, because it combines the Genetic algorithm based method with the Martix based solution method for finding weights. A heuristic segmentation algorithm is initially used to over segment each word. Then the segmentation points are passed through the rule-based module to discard tire incorrect segmentation points and include any missing segmentation points. Following the segmentation the contour is extracted between two correct segmentation points. The contour is passed through the feature extraction module that extracts the angular features. after which the EALS-BT algorithm finds the architecture and the weights for the classifier network. These recognized characters are grouped into words and passed to a variable length lexicon that retrieves words that have the highest confidence value.
Wind energy conversion efficiency has always been an important issue for wind farms. And wind speed calculation is the basic task and key work of wind energy conversion optimization. The cascade clusters of wind turbi...
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Wind energy conversion efficiency has always been an important issue for wind farms. And wind speed calculation is the basic task and key work of wind energy conversion optimization. The cascade clusters of wind turbines are directly related to wind speed, and affected by the terrain, wake disturbance, location distribution and other factors. So it is very difficult to adopt parameter modeling. The cascade characteristics among cluster wind turbines (WTs) are embodied in historical operation data of the WTs. Taking the input wind direction as the initial parameter, we construct the WTs location correlation matrix of the neighborhood distribution relationship of WTs location;we then obtain the correlation relationship of the WTs production wind speed and power by combining the WTs production monitoring data. At the same time, "coupling element" and "aggregation element" WTs can be obtained from the cascade clusters. By verifying the data of a large wind farm, the model proposed in this paper clarifies the relationship between the wind speed and the cascade clusters;using this model, we can calculate the cluster distribution under different wind conditions. It is highly practical and can be applied to other wind farms to support formulation of the efficiency optimization strategies. (C) 2020 Elsevier Ltd. All rights reserved.
This work focuses on using miniature thermoelectric generators encapsulated in a polydimethylsiloxane matrix for designing a bendable, wearable prototype for self-powering a temperature sensor. Therma-TechTM compound ...
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This work focuses on using miniature thermoelectric generators encapsulated in a polydimethylsiloxane matrix for designing a bendable, wearable prototype for self-powering a temperature sensor. Therma-TechTM compound was chosen as the material to form the heatsink to enhance the device bendability. It was tested in real-life scenarios, in indoor and outdoor environments. When the environmental temperature exceeds 30 degrees C, the wearable thermoelectric energy harvester was unable to power the temperature sensor consuming approximately 5 mu W. However, wearing the device on the lower leg can be an interesting approach to differentiate the execution of dynamic activities from static ones using thermoelectric generators. An automatic segmentation algorithm is presented for detecting transitions between motor activities using data only from the thermoelectric generators. Maximum value of load power generated by the prototype is 27 mu W, for a difference of temperature between the thermocouples constituting the thermoelectric generator of 0.23 degrees C, when the environmental temperature was 20.5 degrees C.
A method for searching bridges in IR images is presented in this paper. It is a time-consuming image understanding task to recognize targets in low SCR images. As in IR images, the bridges usually have almost the same...
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A method for searching bridges in IR images is presented in this paper. It is a time-consuming image understanding task to recognize targets in low SCR images. As in IR images, the bridges usually have almost the same gray level range of the background, the typical segmentation algorithm cannot get correct segmentation labels and edge sites of the bridges. The gray level characters of both the lands, which connect the bridge, and the river are fully considered resulting in a method that can be realized effortlessly and quickly. The criteria are also presented to decide whether there exist bridges or not in the given images, so the method endows the system with the ability to seize the target automatically. Some experimental. results are presented demonstrating that the method can effectively recognize bridges in IR images.
作者：
Dong, JiabinJu, YangChina Univ Min & Technol
State Key Lab Geomech & Deep Underground Engn 1 Univ Ave Xuzhou 221116 Jiangsu Peoples R China China Univ Min & Technol Beijing
State Key Lab Coal Resources & Safe Min D11 Xueyuan Rd Beijing 100083 Peoples R China China Univ Min & Technol
Frontier Sci Res Fluidized Min Deep Underground R 1 Univ Ave Xuzhou 221116 Jiangsu Peoples R China China Univ Min & Technol Beijing
State Key Lab Geomech & Deep Underground Engn State Key Lab Coal Resources & Safe Min D11 Xueyuan Rd Beijing 100083 Peoples R China
Fluid flow through rock media is highly significant in underground water management, the geothermal recovery process, and various underground engineering applications. Fractures have a critical effect on the fluid flo...
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Fluid flow through rock media is highly significant in underground water management, the geothermal recovery process, and various underground engineering applications. Fractures have a critical effect on the fluid flow through low-permeability rocks since they serve as the major flow channels in the rock formation. Consequently, the evaluation of fracture permeability is crucial to many engineering applications, such as the geothermal recovery process, exploitation of hydrocarbon resources, and various underground engineering applications. However, fluid flow through rough fractures is complex under the effects of rough profiles and variable apertures. The variation of fracture apertures causes the nonlinear distribution of the pressure along the fracture and thus intensifies the difficulties of studying the flow in fractures. In this study, variable-aperture fractures were simplified as axisymmetric fractures using the Weierstrass-Mandelbrot function. To address the nonlinear distribution of pressure caused by aperture variations, a method is proposed to segment fractures with variable lengths by considering the weights of fracture apertures. With the segmented results, we evaluated the permeability of rough fractures using a modified local law. The evaluation results aligned with the lattice Boltzmann simulation results. Finally, combining the analytical solution of flow through asymmetric fractures with sinusoidal profiles, the proposed methods were thereby validated.
In this paper the authors describe the results of their investigation into the development of a recognition algorithm for identifying numerals that may be isolated or connected, broken or continuous. Using a structura...
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In this paper the authors describe the results of their investigation into the development of a recognition algorithm for identifying numerals that may be isolated or connected, broken or continuous. Using a structural classification scheme, the recognition algorithm is derived as a tree classifier. In an extensive test experiment, an accuracy of 99% was realized with isolated numerals. When connected numerals were also included a recognition accuracy of 93% was obtained.
A fast method of handwritten word recognition suitable for real time applications is presented in this paper. Preprocessing, segmentation and feature extraction are implemented using a chain code representation of the...
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A fast method of handwritten word recognition suitable for real time applications is presented in this paper. Preprocessing, segmentation and feature extraction are implemented using a chain code representation of the word contour. Dynamic matching between characters of a lexicon entry and segment(s) of the input word image is used to rank the lexicon entries in order of best match. Variable duration for each character is defined and used during the matching. Experimental results prove that our approach using the variable duration outperforms the method using fixed duration in terms of both accuracy and speed. Speed of the entire recognition process is about 200 msec on a single SPARC-IO platform and the recognition accuracy is 96.8 percent are achieved for lexicon size of 10, on a database of postal words captured at 212 dpi.
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