Vibration-Based Pattern Password Approach for Visually Impaired People

The pattern password method is amongst the most attractive authentication methods and involves drawing a pattern;this is seen as easier than typing a password.However,since people with visual impairments have been increasing their usage of smart devices,this method is inaccessible for them as it requires them to select points on the touch screen.Therefore,this paper exploits the haptic technology by introducing a vibration-based pattern password approach in which the vibration feedback plays an important role.This approach allows visually impaired people to use a pattern password through two developed vibration feedback:pulses,which are counted by the user,and duration,which has to be estimated by the user.In order to make the proposed approach capable to prevent shoulder-surfing attacks,a camouflage pattern approach is applied.An experimental study is conducted to evaluate the proposed approach,the results of which show that the vibration pulses feedback is usable and resistant to shoulder-surfing attacks.

A correlation between pulse diagnosis of human body and health monitoring of structures

The concept of health monitoring is a key aspect of the field of medicine that has been practiced for a long time. A commonly used diagnostic and health monitoring practice is pulse diagnosis, which can be traced back approximately five thousand years in the recorded history of China. With advances in the development of modern technology, the concept of health monitoring of a variety of engineering structures in several applications has begun to attract widespread attention. Of particular interest in this study is the health monitoring of civil structures. It seem natural, and even beneficial, that these two health-monitoring methods, one as applies to the human body and the other to civil structures, should be analyzed and compared. In this paper, the basic concepts and theories of the two monitoring methods are first discussed. Similarities are then summarized and commented upon. It is hoped that this correlation analysis may help provide structural engineers with some insights into the intrinsic concept of using pulse diagnosis in human health monitoring, which may of be some benefit in the development of modern structural health monitoring methods.

Delamination Identification for FRP Composites with Emphasis on Frequency-Based Vibration Monitoring-A Review

Fibre reinforced polymer (FRP) composite laminates are now commonly usedin many structural applications, especially in the aerospace industry, where margins ofsafety are kept low in order to minimise weight. Timely detection and assessment ofdamage (in particular delaminations) in composite laminates are therefore critical, as theycan cause loss of structural integrity affecting the safe operation of the composite structures.The current trend is towards implementation of structural health monitoring (SHM)systems which can monitor the structures in situ without down time. In this paper, first, thecurrent available SHM techniques for delamination detection in FRP composites arebriefly reviewed, including acoustic emission, fibre optic sensors, Lamb wave-,impedance- and vibration-based methods. Among different vibration-based methods,frequency monitoring is the simplest to implement, requiring only single pointmeasurement, and is relatively accurate and reliable, thus it becomes the main focus ofpresent paper. A comprehensive review of frequency-based vibration monitoring isconducted in terms of the various aspects of delamination identification in FRPs throughfrequency shifts, including review of theoretical models for free vibration of delaminatedFRP beams, survey of finite element modelling of delaminated composite structures,summary of experimental modal analyses on FRP composites with delaminations, andinverse algorithms for frequency-based delamination assessment. This paper aims to helpthe readers to get an overview of the available SHM techniques for monitoring the integrityof FRP composites, with a special emphasis on delamination assessment throughfrequency-based vibration monitoring.

Vehicle-Bridge Interaction Simulation and Damage Identification of a Bridge Using Responses Measured in a Passing Vehicle by Empirical Mode Decomposition Method

To prevent early bridge failures, effective Structural Health Monitoring (SHM) is vital. Vibration-based damage assessment is a powerful tool in this regard, as it relies on changes in a structure’s dynamic characteristics as it degrades. By measuring the vibration response of a bridge due to passing vehicles, this approach can identify potential structural damage. This dissertation introduces a novel technique grounded in Vehicle-Bridge Interaction (VBI) to evaluate bridge health. It aims to detect damage by analyzing the response of passing vehicles, taking into account VBI. The theoretical foundation of this method begins with representing the bridge’s superstructure using a Finite Element Model and employing a half-car dynamic model to simulate the vehicle with suspension. Two sets of motion equations, one for the bridge and one for the vehicle are generated using the Finite Element Method, mode superposition, and D’Alembert’s principle. The combined dynamics are solved using the Newmark-beta method, accounting for road surface roughness. A new approach for damage identification based on the response of passing vehicles is proposed. The response is theoretically composed of vehicle frequency, bridge natural frequency, and a pseudo-frequency component related to vehicle speed. The Empirical Mode Decomposition (EMD) method is applied to decompose the signal into its constituent parts, and damage detection relies on the Intrinsic Mode Functions (IMFs) corresponding to the vehicle speed component. This technique effectively identifies various damage scenarios considered in the study.

Damage Identification of Wind Turbine Blades–A Brief Review

The increasing size of these blades of wind turbines emphasizes the need for reliable monitoring and maintenance.This brief review explores the detection and analysis of damage in wind turbine blades.The study highlights various techniques,including acoustic emission analysis,strain signal monitoring,and vibration analysis,as effective approaches for damage detection.Vibration analysis,in particular,shows promise for fault identification by analyzing changes in dynamic characteristics.Damage indices based on modal properties,such as natural frequencies,mode shapes,and curvature,are discussed.

A deep neural network based surrogate model for damage identification in full-scale structures with incomplete noisy measurements

The paper introduces a novel approach for detecting structural damage in full-scale structures using surrogate models generated from incomplete modal data and deep neural networks(DNNs).A significant challenge in this field is the limited availability of measurement data for full-scale structures,which is addressed in this paper by generating data sets using a reduced finite element(FE)model constructed by SAP2000 software and the MATLAB programming loop.The surrogate models are trained using response data obtained from the monitored structure through a limited number of measurement devices.The proposed approach involves training a single surrogate model that can quickly predict the location and severity of damage for all potential scenarios.To achieve the most generalized surrogate model,the study explores different types of layers and hyperparameters of the training algorithm and employs state-of-the-art techniques to avoid overfitting and to accelerate the training process.The approach’s effectiveness,efficiency,and applicability are demonstrated by two numerical examples.The study also verifies the robustness of the proposed approach on data sets with sparse and noisy measured data.Overall,the proposed approach is a promising alternative to traditional approaches that rely on FE model updating and optimization algorithms,which can be computationally intensive.This approach also shows potential for broader applications in structural damage detection.