Impedance-Based Health Monitoring with Artificial Neural Networks

ثبت نشده
چکیده

One of the important aspects of structural health monitoring is that the technique provides information on the life expectancy of structures, as well as detects and locates structural damage. In general, this requires knowledge of the model of structures in great detail, which is not always possible. In addition, dynamic systems usually present non-linear characteristics, imposing a difficulty on detecting and identifying structural damage for model-based damage detection techniques.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Damage detection and structural health monitoring of ST-37 plate using smart materials and signal processing by artificial neural networks

Structural health monitoring (SHM) systems operate online and test different materials using ultrasonic guided waves and piezoelectric smart materials. These systems are permanently installed on the structures and display information on the monitor screen. The user informs the engineers of the existing damage after observing signal loss which appears after damage is caused. In this paper health...

متن کامل

Simultaneous Monitoring of Multivariate-Attribute Process Mean and Variability Using Artificial Neural Networks

In some statistical process control applications, the quality of the product is characterized by thecombination of both correlated variable and attributes quality characteristics. In this paper, we propose anovel control scheme based on the combination of two multi-layer perceptron neural networks forsimultaneous monitoring of mean vector as well as the covariance matrix in multivariate-attribu...

متن کامل

Nyquist Plots Prediction Using Neural Networks in Corrosion Inhibition of Steel by Schiff Base

The corrosion inhibition effect of N,N′-bis(n-Hydroxybenzaldehyde)-1,3-Propandiimine on mild steel has been investigated in 1 M HCl using electrochemical impedance spectroscopy. A predictive model was presented for Nyquist plots using an artificial neural network. The proposed model predicted the imaginary impedance based on the real part of the impedance as a function of time. The model to...

متن کامل

AN INTELLIGENT FAULT DIAGNOSIS APPROACH FOR GEARS AND BEARINGS BASED ON WAVELET TRANSFORM AS A PREPROCESSOR AND ARTIFICIAL NEURAL NETWORKS

In this paper, a fault diagnosis system based on discrete wavelet transform (DWT) and artificial neural networks (ANNs) is designed to diagnose different types of fault in gears and bearings. DWT is an advanced signal-processing technique for fault detection and identification. Five features of wavelet transform RMS, crest factor, kurtosis, standard deviation and skewness of discrete wavelet co...

متن کامل

Monitoring of Regional Low-Flow Frequency Using Artificial Neural Networks

Ecosystem of arid and semiarid regions of the world, much of the country lies in the sensitive and fragile environment Canvases are that factors in the extinction and destruction are easily destroyed in this paper, artificial neural networks (ANNs) are introduced to obtain improved regional low-flow estimates at ungauged sites. A multilayer perceptron (MLP) network is used to identify the funct...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2000