Health Monitoring of a Benchmark Structure Using Vibration Data

2011 ◽  
pp. 1053-1058
Author(s):  
B. Gunes
Keyword(s):  
Health Monitoring ◽  
Vibration Data

The use of vibration data for liquid rocket health monitoring

1998 ◽  
Author(s):  
Paulo Lozano ◽  
Manuel Martinez-Sanchez ◽  
Nhut Ho ◽  
Rami Mangoubi
Keyword(s):  
Health Monitoring ◽  
Vibration Data ◽  
Liquid Rocket

scholarly journals Assessment of low-cost wireless sensors for structural health monitoring applications

2021 ◽  
Vol 14 (2) ◽  
Author(s):  
Emerson Toledo Júnior ◽  
Alexandre Cury ◽  
Jánes Landre Júnior
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Low Cost ◽  
Tall Buildings ◽  
Raspberry Pi ◽  
Structural Health ◽  
Vibration Data ◽  
Structural Problems ◽  
Implementation Costs ◽  
Wireless Sensing System

Abstract Structural Health Monitoring (SHM) programs play an essential task in the field of civil engineering, especially for assessing safety conditions involving large structures such as viaducts, bridges, stadiums, and tall buildings. In fact, some of these structures are monitored 24 hours a day, 7 days a week, to supply dynamic measurements that can be used for the identification of structural problems, e.g., presence of cracks, excessive vibration, damage, among others. SHM programs may provide automated assessment of structural health by processing vibration data obtained from sensors attached to the structure. Frequently, SHM uses wired systems, which are usually expensive due to the necessity of continuous maintenance and are not always suitable for sensing remote structures. Conversely, commercial wireless systems often demand high implementation costs. Hence, this paper proposes the use of a low-cost wireless sensing system based on the single board computer Raspberry Pi, which significantly reduces implementation expenses while keeping data’s integrity. The wireless communication is performed in real-time through a local wireless network, responsible for sending and receiving vibration data. The proposed system is validated by comparing its results with a commercial wired system through a series of controlled experimental applications. The results suggest that the proposed system is suitable for civil SHM applications.

An Automated Edge Computing-Based Condition Health Monitoring System: With an Application on Rolling Element Bearings

2021 ◽  
Vol 143 (7) ◽  
Author(s):  
Niklas Tritschler ◽  
Andrew Dugenske ◽  
Thomas Kurfess
Keyword(s):  
Monitoring System ◽  
Health Monitoring ◽  
Vibration Signal ◽  
Vibration Sensor ◽  
Vibration Measurement ◽  
Rolling Element Bearings ◽  
Health Monitoring System ◽  
Vibration Data ◽  
Rolling Element ◽  
Vibration Signature

Abstract A failure of rolling element bearings is a frequent cause of machine breakdowns and results in a production loss due to the sudden failure. A regular condition health monitoring and an associated detection of bearing defects in the early stages can be used to predict such sudden failures. To monitor the bearing's condition, the generated vibration signature can be analyzed, since rotating machines have, in most instances, a unique vibration signature that relates to their health status. Presently, bearing analysis of many machines results in significant cost and complexity due to a large amount of vibration data that must be analyzed. A condition health monitoring system (CMS) was developed to automate and simplify the whole process from the vibration measurement to the analysis results. Additionally, the CMS is embedded into an Internet of Things (IoT) architecture. Thereby, a location-independent control of the CMS, the vibration data, and the analysis results is possible. The embedding of sensors can cause communication problems from the sensor to the cloud due to the low bandwidth of sensors and the amount of data that must be transmitted. To overcome this issue, an edge device that acts as a gateway between the vibration sensor and the cloud is the core of the CMS. It measures the vibration signal locally, analyzes it automatically, and publishes a feedback as to the bearing condition to the cloud.

A Simplified Methodology for Condition Assessment of Bridge Bearings Using Vibration Based Structural Health Monitoring Techniques

2021 ◽  
pp. 2150133
Author(s):  
Babar Nasim Khan Raja ◽  
Saeed Miramini ◽  
Colin Duffield ◽  
Shilun Chen ◽  
Lihai Zhang
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Condition ◽  
Condition Assessment ◽  
Concrete Bridges ◽  
Traffic Loading ◽  
Structural Health ◽  
Vibration Data ◽  
Bridge Bearing ◽  
Bridge Bearings

The mechanical properties of bridge bearings gradually deteriorate over time resulting from daily traffic loading and harsh environmental conditions. However, structural health monitoring of in-service bridge bearings is rather challenging. This study presents a bridge bearing condition assessment framework which integrates the vibration data from a non-contact interferometric radar (i.e. IBIS-S) and a simplified analytical model. Using two existing concrete bridges in Australia as a case study, it demonstrates that the developed framework has the capability of detecting the structural condition of the bridge bearings in real-time. In addition, the results from a series of parametric studies show that the effectiveness of the developed framework is largely determined by the stiffness ratio between bridge bearing and girder ([Formula: see text], i.e. the structural condition of the bearings can only be effectively captured when the value of [Formula: see text] ranges from 1/100 and 100.

scholarly journals Enabling Health Monitoring Approach Based on Vibration Data for Accurate Prognostics

2015 ◽  
Vol 62 (1) ◽  
pp. 647-656 ◽  
Author(s):  
Kamran Javed ◽  
Rafael Gouriveau ◽  
Noureddine Zerhouni ◽  
Patrick Nectoux
Keyword(s):  
Health Monitoring ◽  
Vibration Data

Obtaining Vibration Data for Autonomous Health Monitoring of Interplanetary Drills

2016 ◽  
Author(s):  
Dean Bergman ◽  
Brian J. Glass ◽  
Thomas Stucky ◽  
Kris Zacny ◽  
Gale Paulsen ◽  
...  
Keyword(s):  
Health Monitoring ◽  
Vibration Data

Application of Compressive Sampling for Accelerometer Signals Used in Structural Health Monitoring

2009 ◽  
Vol 413-414 ◽  
pp. 455-462 ◽  
Author(s):  
Yue Quan Bao ◽  
James L. Beck ◽  
Hui Li
Keyword(s):  
Structural Health Monitoring ◽  
Data Compression ◽  
Health Monitoring ◽  
Yellow River ◽  
Compressive Sampling ◽  
Sensor Data ◽  
Huffman Coding ◽  
Civil Structures ◽  
Structural Health ◽  
Vibration Data

In structural health monitoring (SHM) of civil structures, data compression is often needed for saving the cost of data transfer and storage because of the large volumes of sensor data generated from the monitoring system. The traditional framework for data compression is to first sample the full signal, then to compress it. Recently, a new data compression method named compressive sampling (CS) has been presented, that can acquire the data directly in compressed form by using special sensors. In this paper, the potential of CS for data compression of vibration data is investigated using simulation of the CS sensor algorithm. The acceleration data collected from the SHM system of Shandong Binzhou Yellow River Highway Bridge is used to analyse the data compression ability of CS. For comparison, the wavelet transform based and Huffman coding methods are also employed to compress the data. The results show that CS is useful for compression of vibration data in SHM of civil structures.

On the use of symbolic vibration data for robust structural health monitoring

2016 ◽  
Vol 169 (9) ◽  
pp. 715-723 ◽  
Author(s):  
Vinicius Alves ◽  
Alexandre Cury ◽  
Christian Cremona
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Health ◽  
Vibration Data
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