Identification of internal damages in reinforced concrete slabs using probability density field of acoustic emission events

To assess the structural capacity of reinforced concrete structures, identifying the internal cracks is important. Acoustic emission (AE) is promising to estimate the location of internal cracks. However, the localization is influenced by many factors like arrival time picking error, presence of crack, etc., resulting in localization error. The...

Investigation of concrete crack kinematics through probability density field of the location of acoustic emission events

Monitoring or identifying structural cracks is crucial for assessing the health of existing concrete structures. Key information about structural cracking encompasses the location of the crack and its kinematics, which include movements perpendicular and parallel to the crack face. Acoustic emission (AE) is a sensitive technique for detecting...

Developing a new acoustic emission source classification criterion for concrete structures based on signal parameters

Acoustic emission (AE) signal parameters can be used to classify the source type in concrete structures. However, signal parameters are influenced by the wave propagation from the source to the receiver, leading to wrong source classification results, especially for monitoring large concrete structures. This paper experimentally evaluates the...

Probability density field of acoustic emission events: Damage identification in concrete structures

This paper proposes a new damage identification method, namely, the probability density field of acoustic emission (AE) events. This new method provides a different perspective to deal with the uncertainties in the source localization process. We treat the source location as a random variable, and estimate its probability density field based...

Acoustic Emission-based crack tracking for existing concrete structures: Influence of number of load cycles and loading speed

Acoustic Emission (AE)-based crack tracking is a promising approach to locate cracks in concrete structures. Different from conventional AE, this approach uses AE activities during crack closure. But, AE activities during crack closure may be influenced by the number of load cycles and loading speed. This may challenge the applicability of AE...

A Study on Reference Microphone Selection for Multi-Microphone Speech Enhancement

Multi-microphone speech enhancement methods typically require a reference position with respect to which the target signal is estimated. Often, this reference position is arbitrarily chosen as one of the reference microphones. However, it has been shown that the choice of the reference microphone can have a significant impact on the final...

Sensor selection and rate distribution based beamforming in wireless acoustic sensor networks

Power usage is an important aspect of wireless acoustic sensor networks (WASNs) and reducing the amount of information that is to be transmitted is one effective way to save it. In previous contributions, we presented sensor selection as well as rate distribution methods to reduce the power usage of beamforming algorithms in WASNs. Taking...

Distributed Rate-Constrained LCMV Beamforming

In this letter, we propose a decentralized framework for rate-distributed linearly constrained minimum variance (LCMV) beamforming in wireless acoustic sensor networks. To save the energy usage within the network, we propose to minimize the transmission cost and put a constraint on the noise reduction performance. Subsequently, we...

Relative Acoustic Transfer Function Estimation in Wireless Acoustic Sensor Networks

In this paper, we present an algorithm to estimate the relative acoustic transfer function (RTF) of a target source in wireless acoustic sensor networks (WASNs). Two well-known methods to estimate the RTF are the covariance subtraction (CS) method and the covariance whitening (CW) approach, the latter based on the generalized eigenvalue...

Rate-Distributed Spatial Filtering Based Noise Reduction in Wireless Acoustic Sensor Networks

In wireless acoustic sensor networks (WASNs), sensors typically have a limited energy budget as they are often battery driven. Energy efficiency is therefore essential to the design of algorithms in WASNs. One way to reduce energy costs is to only select the sensors which are most informative, a problem known as sensor selection. In this way,...

Structured Total Least Squares Based Internal Delay Estimation For Distributed Microphone Auto-Localization

Auto-localization in wireless acoustic sensor networks (WASNs) can be achieved by time-of-arrival (TOA) measurements between sensors and sources. Most existing approaches are centralized, and they require a fusion center to communicate with other nodes. In practice, WASN topologies are time-varying with nodes joining or leaving the network,...

Greedy Gossip Algorithm with Synchronous Communication for Wireless Sensor Networks

Randomized gossip (RG) based distributed averaging has been popular for wireless sensor networks (WSNs) in multiple areas. With RG, randomly two adjacent nodes are selected to communicate and exchange information iteratively until consensus is reached. One way to improve the convergence speed of RG is to use greedy gossip with eavesdropping (GGE...