Damage Location Monitoring of Graphene/Conducting Polymer Composites Film Based on Self-Sensing.

Nanomaterials (Basel)

School of Electrical Engineering and Electronic Information, Xihua University, Chengdu 611743, China.

Published: August 2022

Conductive graphene polymer composites are considered promising functional materials in gas detection, strain detection, metal corrosion prevention, and electromagnetic wave absorption, owing to their good flexibility, lightweight, and adjustable conductivity. The internal defects or external damages of composite films will seriously affect the electrical and functional properties of the materials. Based on the conductive network inside the conductive polymer film and the self-inductance to ultrasonic wave, the defect self-monitoring system of the conductive polymer film is designed and optimized in this work. The self-damage detection system is composed of an electrode array, excitation source, resistance signal acquisition and processing circuit, and damage display. Aiming at different scenarios, the improved interdigital structure transducer for sensors and damage detection device for coating film with a large area are presented and optimized respectively. Meanwhile, the damage location algorithm based on time difference measurement and kernel density estimation algorithm is also optimized. The multiple damage detection is realized by a device with a 4 × 8 electrode array, and the relative error of damage area with 1 mm × 1 mm is less than 5%, and the lower detection limits of damage size are 0.3 mm × 0.3 mm.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9412304PMC
http://dx.doi.org/10.3390/nano12162823DOI Listing

Publication Analysis

Top Keywords

damage location
8
polymer composites
8
conductive polymer
8
polymer film
8
electrode array
8
damage detection
8
damage
7
detection
6
location monitoring
4
monitoring graphene/conducting
4

Similar Publications

Introduction: Endoscopic resection is suitable for most benign gastric or early stage cancerous polyps. Laparoscopic local resection is performed only for gastric polyps that are difficult to treat with endoscopic resection, such as recurrent or large polyps. However, when polyps are located in difficult regions, such as the gastric cardia and prepyloric antrum, wedge resection may damage the sphincter around the cardia or pylorus, resulting in postoperative deformity or stenosis.

View Article and Find Full Text PDF

Liver fibrosis is a persistent damage repair response triggered by various etiological factors, resulting in an excessive accumulation of extracellular matrix (ECM). Activated hepatic stellate cells (HpSCs) are the primary source of ECM proteins. Therefore, specifically targeting HpSCs has become a crucial approach for treating liver fibrosis.

View Article and Find Full Text PDF

Background: Recent studies suggest that the anterior limb of the internal capsule may be an area of convergence for multiple compulsion loops. In this study, the role of different dopaminergic compulsion loops in the mechanism of obsessive-compulsive disorder (OCD) was investigated by selectively damaging dopaminergic neurons or fibers in the corresponding targets with 6-hydroxydopamine (6-OHDA) and depicting the anatomical map of various compulsion loops located in the anterior limb of the internal capsule.

Methods: A total of 52 male Sprague Dawley (SD) rats were exposed to either saline (1 mL/kg, NS group, n = 6) or quinpirole (QNP, dopamine D2-agonist, 0.

View Article and Find Full Text PDF

Tiny Machine Learning Implementation for Guided Wave-Based Damage Localization.

Sensors (Basel)

January 2025

Department of Mechanical Engineering, University of Siegen, Paul-Bonatz-Straße 9-11, 57076 Siegen, Germany.

This work leverages ultrasonic guided waves (UGWs) to detect and localize damage in structures using lightweight Artificial Intelligence (AI) models. It investigates the use of machine learning (ML) to train the effects of the damage on UGWs to the model. To reduce the number of trainable parameters, a physical signal processing approach is applied to the raw data before passing the data to the model.

View Article and Find Full Text PDF

The Application of an Intelligent -Harvesting Device Based on FES-YOLOv5s.

Sensors (Basel)

January 2025

Key Laboratory of Modern Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Nanjing Institute of Agricultural Mechanization, Nanjing 210014, China.

To address several challenges, including low efficiency, significant damage, and high costs, associated with the manual harvesting of , in this study, a machine vision-based intelligent harvesting device was designed according to its agronomic characteristics and morphological features. This device mainly comprised a frame, camera, truss-type robotic arm, flexible manipulator, and control system. The FES-YOLOv5s deep learning target detection model was used to accurately identify and locate .

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!