scholarly journals Low-Velocity Impact Localization on a Honeycomb Sandwich Panel Using a Balanced Projective Dictionary Pair Learning Classifier

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2602
Author(s):  
Zhaoyu Zheng ◽  
Jiyun Lu ◽  
Dakai Liang
Keyword(s):  
Carbon Fiber ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Sandwich Panel ◽  
Weight Factor ◽  
Low Velocity ◽  
Honeycomb Sandwich ◽  
Aluminum Honeycomb ◽  
The Impact ◽  
Impact Localization

Carbon-fiber aluminum honeycomb sandwich panels are vulnerable to low-velocity impacts, which can cause structural damage and failures that reduce the bearing performance and reliability of the structure. Therefore, a method for locating such impacts through a sensor network is very important for structural health monitoring. Unlike composite laminates, the stress wave generated by an impact is damped rapidly in a sandwich panel, meaning that the signal qualities measured by different sensors vary greatly, thereby making it difficult to locate the impact. This paper presents a method for locating impacts on carbon-fiber aluminum honeycomb sandwich panels utilizing fiber Bragg grating sensors. This method is based on a projective dictionary pair learning algorithm and uses structural sparse representation for impact localization. The measurement area is divided into several sub-areas, and a corresponding dictionary is trained separately for each sub-area. For each dictionary, the sensors are grouped into main sensors within the sub-area and auxiliary sensors outside the sub-area. A balancing weight factor is added to optimize the proportion of the two types of sensor in the recognition model, and the algorithm for determining the balancing weight factor is designed to suppress the negative effects on the positioning of the sensors with poor signal quality. The experimental results show that on a 300 mm × 300 mm × 15 mm sandwich panel, the impact positioning accuracy of this method is 96.7% and the average positioning error is 0.85 mm, which are both sufficient for structural health monitoring.

Structural Health Monitoring for Carbon Fiber/Carbon Nanotube (CNT)/Epoxy Composite Sensor

2006 ◽  
Vol 321-323 ◽  
pp. 290-293 ◽  
Author(s):  
Sang Il Lee ◽  
Dong Jin Yoon
Keyword(s):  
Electrical Resistivity ◽  
Carbon Nanotube ◽  
Carbon Fiber ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Epoxy Composite ◽  
Structural Safety ◽  
Structural Health ◽  
Nanotube Composites ◽  
Carbon Fiber Epoxy

Structural health monitoring for carbon nanotube (CNT)/carbon fiber/epoxy composite was verified by the measurement of electrical resistivity. This study has focused on the preparation of carbon nanotube composite sensors and their application for structural health monitoring. The change of the electrical resistance was measured by a digital multimeter under tensile loads. Although a carbon fiber was broken, the electrical connection was still kept by distributed CNT particles in the model composites. As the number of carbon fiber breakages increased, electrical resistivity was stepwise increased. The CNT composites were well responded with fiber damages during the electro-micromechnical test. Carbon nanotube composites can be useful sensors for structural health monitoring to diagnose a structural safety and to prevent a collapse.

scholarly journals Structural Health Monitoring for cultural heritage constructions: a resilience perspective

2019 ◽  
Author(s):  
Maria Pina Limongelli ◽  
Zehra Irem Turksezer ◽  
Pier Francesco Giordano
Keyword(s):  
Structural Health Monitoring ◽  
Cultural Heritage ◽  
Health Monitoring ◽  
Social Value ◽  
Specific Reference ◽  
Structural Health ◽  
Heritage Constructions ◽  
The Impact ◽  
Support Decision Making ◽  
Over Time

<p>Disturbances or disruptive events may induce reductions of functionality of the built environment. For Cultural Heritage (CH) structures, functionalities may range from technical, to economic ones linked to touristic activities, up to intangible functionalities related to the cultural and social value of these constructions. Resilience can be defined as the capability of a system overcome a disturbance with the minimum total loss of functionality over time. Structural Health Monitoring (SHM) may enhance resilience by providing information that can support decision making, aiming to reduce the impact of the disturbances. In this paper, the benefits of SHM systems as means for improving resilience of CH structures are addressed and discussed with specific reference to the three different decision situations; before, during and after events of disturbances. Examples of real applications of SHM for CH structures and its effect on the resilience of the system conclude the paper.</p>

scholarly journals Development of an automated assessment technology for detecting damage in body armour

2020 ◽  
Vol 234 (20) ◽  
pp. 4116-4125
Author(s):  
Ryan Marks ◽  
Stephen Grigg ◽  
Davide Crivelli ◽  
Matthew Pearson ◽  
Mark Eaton ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Ultrasonic Waves ◽  
Baseline Measurement ◽  
Automated Assessment ◽  
Central Location ◽  
Body Armour ◽  
Low Profile ◽  
The Impact ◽  
Plate Current

Hard ballistic body armour plates are designed to withstand the impact of a bullet and protect the wearer, if this happens the armour is clearly damaged and so is retired from service. Mishandling, however, such as dropping the armour, may cause minor and difficult to detect damage which compromises the effectiveness of the plate. Current methods of inspection involve shipping the plates to a central location, performing a thorough inspection and returning them to service if uncompromised; this is costly and requires redundancy of equipment for when not in service. Acousto-Ultrasonics is a method of structural health monitoring in which ultrasonic waves are excited in a structure by a transducer and receivers record the response, any deviation from a baseline measurement give an indication of damage within the structure. Within this paper the development and testing of a novel handheld prototype device is presented, which gives a simple yes/no answer to if there is damage on the plate. This inspection is quick and easy to perform by unskilled personnel. Low profile sensors have been utilised combined with a novel flexible circuitry with built in memory, which does not compromise the effectiveness of the armour.

Dynamic Fracture Analysis of Aluminum Honeycomb Sandwich Panel

2006 ◽  
pp. 67-72
Author(s):  
Byung Il Kim ◽  
Byeong Wook Noh ◽  
Young Woo Choi ◽  
Sung In Bae ◽  
Jung Il Song
Keyword(s):  
Dynamic Fracture ◽  
Sandwich Panel ◽  
Fracture Analysis ◽  
Honeycomb Sandwich ◽  
Aluminum Honeycomb

An Impact-Based Experimental Setup for Evaluation of Rapid Electromechanical Impedance-Based Structural Health Monitoring

2020 ◽  
Author(s):  
Mohammad Alshaikh Ali ◽  
Eric C. Nolan ◽  
Steven R. Anton ◽  
Mohsen Safaei
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Sampling Rate ◽  
Frequency Resolution ◽  
Experimental Setup ◽  
Frequency Bandwidth ◽  
Electromechanical Impedance ◽  
Excitation Signal ◽  
Structural Health ◽  
The Impact

Abstract This work investigates the application of structural health monitoring (SHM) in a dynamic environment with the electromechanical impedance (EMI) method. Classically, the EMI method monitors civil or mechanical structures for damage in static environments. Advances in data acquisition (DAQ) now allow the possibility of rapid damage detection in dynamic environments. An impact-based experimental setup is developed to create a repeatable dynamic event through a collision between a pneumatically actuated striker bar and a static incident bar instrumented with a piezoelectric transducer. The EMI method is employed to detect the change of state at the interface of the two colliding bars. Experimental results prove the pneumatic launching system is capable of repeatable dynamic events, but the duration of contact is only 0.03 ms and the current DAQ system is incapable of detecting the event. A 3D printed programming material interface is placed at the location of impact to increase the duration of contact to approximately 1 ms. An excitation signal is created to continuously sweep a 0.5 ms chirp signal with a frequency bandwidth from 60–70 kHz (previously identified damage sensitive frequency bandwidth from static testing) for 7.5 seconds. Results indicate that due to the sampling rate and sweep time of the excitation signal, the frequency resolution is not adequate to properly assess if the impact is detected. Improvements in the DAQ hardware must be considered for future work.

Impact Detection Using an Array of Piezoelectric Wafer Active Sensors and a Microcontroller Unit

2010 ◽  
Author(s):  
Abraham Light-Marquez ◽  
Andrei Zagrai
Keyword(s):  
Structural Health Monitoring ◽  
Sensor Network ◽  
Health Monitoring ◽  
Detection System ◽  
Active Sensors ◽  
Structural Health ◽  
Impact Detection ◽  
Piezoelectric Wafer Active Sensors ◽  
Piezoelectric Wafer ◽  
The Impact

This report discusses the development of an embeddable impact detection system utilizing an array of piezoelectric wafer active sensors (PWAS) and a microcontroller. Embeddable systems are a critical component to successfully implement a complete and robust structural health monitoring system. System capabilities include impact detection, impact location determination and digitization of the impact waveform. A custom algorithm was developed to locate the site of the impact.. The embedded system has the potential for additional capabilities including advanced signal processing and the integration of wireless functionality. For structural health monitoring applications it is essential to determine the extent of damage done to the structure. In an attempt to determine these parameters a series of impact tests were conducted using a ball drop tower on a square aluminum plate. The response of the plate to the impact event was recorded using a piezoelectric wafer sensor network attached to the surface of the plate. From this testing it was determined that several of the impact parameters are directly correlated with the features recorded by the sensor network.

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