Advanced signal processing for high temperatures health monitoring of condensed water height in steam pipes

2013 ◽  
Author(s):  
Shyh-Shiuh Lih ◽  
Yoseph Bar-Cohen ◽  
Hyeong Jae Lee ◽  
Nobuyuki Takano ◽  
Xiaoqi Bao
Keyword(s):  
Signal Processing ◽  
High Temperatures ◽  
Health Monitoring ◽  
Condensed Water ◽  
Steam Pipes ◽  
Water Height

High temperatures health monitoring of the condensed water height in steam pipe systems

2013 ◽  
Author(s):  
Hyeong Jae Lee ◽  
Yoseph Bar-Cohen ◽  
Shyh-Shiuh Lih ◽  
Mircea Badescu ◽  
Xiaoqi Bao ◽  
...  
Keyword(s):  
High Temperatures ◽  
Health Monitoring ◽  
Condensed Water ◽  
Steam Pipe ◽  
Pipe Systems ◽  
Water Height

Development and Testing of a Multitransducer System for Measuring Height of Condensed Water in Steam Pipes With Steady-State and Turbulent Flow Conditions

2018 ◽  
Vol 1 (3) ◽  
Author(s):  
Shyh-Shiuh Lih ◽  
Hyeong Jae Lee ◽  
Yoseph Bar-Cohen ◽  
Mircea Badescu
Keyword(s):  
Signal Processing ◽  
Steady State ◽  
Turbulent Flow ◽  
In Situ Monitoring ◽  
Flow Conditions ◽  
Dynamic Surface ◽  
Steam Pipes ◽  
Turbulent Flow Conditions ◽  
Water Height

A system consisting of a multiplexer and multiple ultrasonic probes was developed for in situ monitoring of the water condensation height in steam pipes under steady-state and turbulent flow conditions. The measurement method, the signal processing techniques, the experimental setup, and the test results are presented in this paper. The feasibility and efficiency of the developed multitransducers and signal processing algorithms were demonstrated. The measured water height and wave pattern in dynamic surface conditions inside the pipe were verified through the snapshot of the recorded video images. The developed methodology built the framework for the use of multiple transducers array ultrasonic system for practical application to in situ monitor the water height in steam pipes.

Time–frequency and time–scale analyses for structural health monitoring

2006 ◽  
Vol 365 (1851) ◽  
pp. 449-477 ◽  
Author(s):  
Wiesław J Staszewski ◽  
Amy N Robertson
Keyword(s):  
Signal Processing ◽  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Time Scale ◽  
Time Frequency ◽  
Structural Health ◽  
Variant Analysis

Signal processing is one of the most important elements of structural health monitoring. This paper documents applications of time-variant analysis for damage detection. Two main approaches, the time–frequency and the time–scale analyses are discussed. The discussion is illustrated by application examples relevant to damage detection.

High temperature monitoring the height of condensed water in steam pipes

2011 ◽  
Author(s):  
Yoseph Bar-Cohen ◽  
Shyh-Shiuh Lih ◽  
M. Badescu ◽  
Xiaoqi Bao ◽  
Stewart Sherrit ◽  
...  
Keyword(s):  
High Temperature ◽  
Temperature Monitoring ◽  
Condensed Water ◽  
Steam Pipes

scholarly journals Application of Machine Learning with Impedance Based Techniques for Structural Health Monitoring of Civil Infrastructure

2019 ◽  
Vol 8 (6S4) ◽  
pp. 1139-1148
Keyword(s):  
Machine Learning ◽  
Signal Processing ◽  
Structural Health Monitoring ◽  
Damage Detection ◽  
Soft Computing ◽  
Health Monitoring ◽  
Multiple Cracks ◽  
Civil Infrastructure ◽  
Structural Health ◽  
Soft Computing Techniques

Increased attentiveness on the environmental and effects of aging, deterioration and extreme events on civil infrastructure has created the need for more advanced damage detection tools and structural health monitoring (SHM). Today, these tasks are performed by signal processing, visual inspection techniques along with traditional well known impedance based health monitoring EMI technique. New research areas have been explored that improves damage detection at incipient stage and when the damage is substantial. Addressing these issues at early age prevents catastrophe situation for the safety of human lives. To improve the existing damage detection newly developed techniques in conjugation with EMI innovative new sensors, signal processing and soft computing techniques are discussed in details this paper. The advanced techniques (soft computing, signal processing, visual based, embedded IOT) are employed as a global method in prediction, to identify, locate, optimize, the damage area and deterioration. The amount and severity, multiple cracks on civil infrastructure like concrete and RC structures (beams and bridges) using above techniques along with EMI technique and use of PZT transducer. In addition to survey advanced innovative signal processing, machine learning techniques civil infrastructure connected to IOT that can make infrastructure smart and increases its efficiency that is aimed at socioeconomic, environmental and sustainable development.

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