Sensor placement with optimal damage detectability for statistical damage detection

In this paper the investigation of a structural health monitoring method for thin-walled parts of structures is presented. The concept is based on the guided elastic wave propagation phenomena. This type of waves can be used in order to obtain information about structure condition and possibly damaged areas. Guided elastic waves can travel in the medium with relatively low attenuation, therefore they enable monitoring of extensive parts of structures. In this way it is possible to detect small defects in their early stage of growth. It is essential because undetected damage can endanger integrity of a structure. In reported investigation piezoelectric transducer was used to excite guided waves in chosen specimens. Dispersion of guided waves results in changes of velocity with the wave frequency, therefore a narrowband signal was used. Measurement of the wave field was realized using laser scanning vibrometer that registered the velocity responses at points belonging to a defined mesh. An artificial discontinuity was introduced to the specimen. The goals of the investigation was to detect it and find optimal sensor placement for this task. Determination of the optimal placement of sensors is a very challenging mission. In conducted investigation laser vibrometer was used to facilitate the task. The chosen mesh of measuring points was the basis for the investigation. The purpose was to consider various configuration of piezoelectric sensors. Instead of using vast amount of piezoelectric sensors the earlier mentioned laser vibrometer was used to gather the necessary data from wave propagation. The signals gather by this non-contact method for the considered network were input to the damage detection algorithm. Damage detection algorithm was based on a procedure that seeks in the signals the damage-reflected waves. Knowing the wave velocity in considered material the damage position can be estimated.

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2-D Statistical Damage Detection of Concrete Structures Combining Smart Piezoelectric Materials and Scanning Laser Doppler Vibrometry

Structural Durability & Health Monitoring ◽

10.32604/sdhm.2018.04607 ◽

2018 ◽

Vol 12 (4) ◽

pp. 257-279

Author(s):

Costas P. Providakis ◽

Stavros E. Tsistrakis ◽

Evangelos V. Liarakos

Keyword(s):

Damage Detection ◽

Piezoelectric Materials ◽

Concrete Structures ◽

Laser Doppler ◽

Scanning Laser ◽

Laser Doppler Vibrometry ◽

Statistical Damage

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Optimal Sensor Placement for Damage Detection in Complex Structures

Volume 2: Multifunctional Materials; Enabling Technologies and Integrated System Design; Structural Health Monitoring/NDE; Bio-Inspired Smart Materials and Structures ◽

10.1115/smasis2009-1419 ◽

2009 ◽

Cited By ~ 2

Author(s):

Sunilkumar Soni ◽

Santanu Das ◽

Aditi Chattopadhyay

Keyword(s):

False Alarm ◽

Damage Detection ◽

False Alarm Rate ◽

Structural Component ◽

Detection Rate ◽

Sensor Placement ◽

False Alarms ◽

Optimal Sensor Placement ◽

Detection Scheme ◽

Sensing Radius

An optimal sensor placement methodology is proposed based on detection theory framework to maximize the detection rate and minimize the false alarm rate. Minimizing the false alarm rate for a given detection rate plays an important role in improving the efficiency of a Structural Health Monitoring (SHM) system as it reduces the number of false alarms. The placement technique is such that the sensor features are as directly correlated and as sensitive to damage as possible. The technique accounts for a number of factors, like actuation frequency and strength, minimum damage size, damage detection scheme, material damping, signal to noise ratio (SNR) and sensing radius. These factors are not independent and affect each other. Optimal sensor placement is done in two steps. First, a sensing radius, which can capture any detectable change caused by a perturbation and above a certain threshold, is calculated. This threshold value is based on Neyman-Pearson detector that maximizes the detection rate for a fixed false alarm rate. To avoid sensor redundancy, a criterion to minimize sensing region overlaps of neighboring sensors is defined. Based on the sensing region and the minimum overlap concept, number of sensors needed on a structural component is calculated. In the second step, a damage distribution pattern, known as probability of failure distribute, is calculated for a structural component using finite element analysis. This failure distribution helps in selecting the most sensitive sensors, thereby removing those making remote contributions to the overall detection scheme.

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