A New Multi-Resolution Wavelet Neural Network For Bridge Health Monitoring

2010 ◽  
Vol 16 (5) ◽  
pp. 771-776
Author(s):  
Fengqing Han ◽  
Jianxi Yang
Keyword(s):  
Neural Network ◽  
Health Monitoring ◽  
Wavelet Neural Network ◽  
Bridge Health Monitoring

scholarly journals Data mining algorithms for bridge health monitoring: Kohonen clustering and LSTM prediction approaches

2019 ◽  
Vol 76 (2) ◽  
pp. 932-947 ◽  
Author(s):  
Aiping Guo ◽  
Ajuan Jiang ◽  
Jie Lin ◽  
Xiaoxiao Li
Keyword(s):  
Neural Network ◽  
Health Monitoring ◽  
Short Term Memory ◽  
Bridge Engineering ◽  
Normal Operation ◽  
Massive Data ◽  
Health State ◽  
Bridge Structure ◽  
Continuous Growth ◽  
Bridge Health Monitoring

Abstract In recent years, bridge health monitoring system has been widely used to deal with massive data produced with the continuous growth of monitoring time. However, how to effectively use these data to comprehensively analyze the state of a bridge and provide early warning of bridge structure changes is an important topic in bridge engineering research. This paper utilizes two algorithms to deal with the massive data, namely Kohonen neural network and long short-term memory (LSTM) neural network. The main contribution of this study is using the two algorithms for health state evaluation of bridges. The Kohonen clustering method is shown to be effective for getting classification pattern in normal operating condition and is straightforward for outliers detection. In addition, the LSTM prediction method has an excellent prediction capability which can be used to predict the future deflection values with good accuracy and mean square error. The predicted deflections agree with the true deflections, which indicate that the LSTM method can be utilized to obtain the deflection value of structure. What’s more, we can observe the changing trend of bridge structure by comparing the predicted value with its limit value under normal operation.

A Neural Network-Based System for Bridge Health Monitoring

2012 ◽  
Vol 452-453 ◽  
pp. 557-563
Author(s):  
Tzu Kang Lin ◽  
Ming Chih Huang ◽  
Jer Fu Wang
Keyword(s):  
Neural Network ◽  
Health Monitoring ◽  
Bridge Health Monitoring

A Neural Network-Based System for Bridge Health Monitoring

2012 ◽  
Vol 452-453 ◽  
pp. 557-563 ◽  
Author(s):  
Tzu Kang Lin ◽  
Ming Chih Huang ◽  
Jer Fu Wang
Keyword(s):  
Neural Network ◽  
Transfer Function ◽  
Monitoring System ◽  
Health Monitoring ◽  
Network Technology ◽  
Health Monitoring System ◽  
Bridge Health Monitoring ◽  
Analytical Results ◽  
Neural Network Technology

A bridge health monitoring system based on neural network technology is proposed in this paper. Two major ground excitations recorded in Taiwan were used to establish the NARX-based system. Analytical results from different methods including transfer function, ARX-based model, and the proposed neural network-based system were used to evaluate the efficiency in health monitoring. The result shows that the proposed system can be used successfully with superior advantages after major earthquakes for bridge health monitoring.

A Local Linear Wavelet Neural Network Based on a Bayesian Design Method

2009 ◽  
Vol 129 (7) ◽  
pp. 1356-1362
Author(s):  
Kunikazu Kobayashi ◽  
Masanao Obayashi ◽  
Takashi Kuremoto
Keyword(s):  
Neural Network ◽  
Design Method ◽  
Wavelet Neural Network ◽  
Bayesian Design ◽  
Local Linear
Sign in / Sign up

Export Citation Format

Share Document