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The purpose of this paper is to employ the acoustic wave propagation method for leakage detection in pipes. The first objective is to use acoustic finite element analysis (AFEA) method to simulate acoustic wave propagation and acoustic wave reflectometry in an intact pipe and in pipes with leaks of various sizes. This is followed by the second objective which is to validate the effectiveness and the practicability of the acoustic wave method via experimental testing. The third objective involves the decomposition and de-noising of the measured acoustic waves using stationary wavelet transform (SWT). It is shown that this approach, which is used for the first time on leakage detection in pipes, can be used to identify, locate and estimate the size of a leakage defect in a pipe.

The research work was designed inline with best practices and acceptable standards. The research methodology focusses on five basic areas: literature review; experimental measurements; simulations; data analysis and writing-up of the study with clear-cut communication of the findings. The approach used was acoustic wave propagation-based method in conjunction with SWT for leakage detection in fluid-filled pipe.

First, the simulation of acoustic wave propagation and acoustic wave reflectometry in fluid-filled pipes with and without leakage have great potential in leakage detection in pipeline systems and can detect very small leaks of 1 mm diameter. Second, the measured noise-contaminated acoustic wave propagation in a fluid-filled pipe can be successfully de-noised using the SWT method in order to clearly identify and locate leakage as little as 5 mm diameter in a pipe. Third, AFEA of a fluid-filled pipe can be achieved with the simulation of only the fluid content of the pipe and without the inclusion of the pipe in the model. This eliminates contact interaction of the solid pipe walls and the fluid, and as a consequence reduces computational time and resources. Fourth, the relationship of the ratio of the leakage diameter to the ratio of the first and second secondary wave amplitudes caused by the leakage can be represented by a second-order polynomial function. Fifth, the identification of leakage in a pipe is intuitive from mere comparison of the acoustic waveforms of an intact pipe with that of a pipe with a leakage.

The research work is a novelty and was developed from the scratch. The AFEA of acoustic wave propagation and acoustic wave reflectometry in a static fluid-filled pipe, and the SWT method have been used for the first time to detect, locate and estimate the size of a leakage in a fluid-filled pipe.

This paper aims to Separation and sorting of biological cells is desirable in many applications for analyzing cell properties, such as disease diagnostics, drugs delivery, chemical processing and therapeutics.

Acoustic energy-based bioparticle separation is a simple, viable, bio-compatible and contact-less technique using, which can separate the bioparticles based on their density and size, with-out labeling the sample particles.

Conventionally available bioparticle separation techniques as fluorescence and immunomagnetic may cause a serious threat to the life of the cells due to various compatibility issues. Moreover, they also require an extra pre-processing labeling step. Contrarily, label-free separation can be considered as an alternative solution to the traditional bio-particle separation methods, due to their simpler operating principles and lower cost constraints. Acoustic based particle separation methods have captured a lot of attention among the other reported label-free particle separation techniques because of the numerous advantages it offers.

This study tries to briefly cover the developments of different acoustic-based particle separation techniques over the years. Unlike the conventional surveys on general bioparticles separation, this study is focused particularly on the acoustic-based particle separation. The study would provide a comprehensive guide for the future researchers especially working in the field of the acoustics, in studying and designing the acoustic-based particle separation techniques.

The study insights a brief theory of different types of acoustic waves and their interaction with the bioparticles is considered, followed by acoustic-based particle separation devices reported till the date. The integration of acoustic-based separation techniques with other methods and with each other is also discussed. Finally, all major aspects like the approach, and productivity, etc., of the adopted acoustic particle separation methods are sketched in this article.

The acousto-ultrasonic approach is used for propagating stress waves through different configurations of CORTEN steel specimens. The propagated waves are recorded and analysed by piezoelectric sensors. The purpose of the study is to study the characteristics of the CORTEN steel by analysing the propagated waves.

To investigate the attenuation in acoustic wave propagation due to the corrosion formation in CORTEN steel specimens and to train a neural network model to classify the attenuated acoustic waves automatically.

Due to the corrosion formation in CORTEN steel specimens, attenuation is observed in amplitude, energy, counts and duration of the propagated waves. When the waves are analysed in their time-frequency characteristics, attenuation is observed in their frequency and spectral energy.

The corrosion formation in CORTEN steel can automatically be analysed by using the acousto-ultrasonic approach and the trained deep learning neural network.

Ion‐acoustic wave propagation in plasma is discussed. Analytical and numerical solutions are given for one‐dimensional plane waves. The similarity of the ion‐acoustic waves to the waves associated with an electrical transmission line is pointed out and the solved examples are compared with experimental observations.

This paper aims to determine the influence of geometrical features of the channel on the acoustic wave generation in a ducted cavity. The analysis is focussed on the effects of the change in the entrance length upstream the cavity and the height. The study is supposed to investigate boundary layer and acoustic wave parameters, and an attempt will be made to determine the correlation between the geometrical dimension and those parameters.

Analysis is conducted with the aim of a computational fluid dynamics (CFD) tool and selected results are validated with experimental investigations. The influence of grid resolution and time discretization is analysed. Four different entrance lengths and height are investigated. Qualitative and quantitative comparison between cases is presented.

The investigations prove the small influence of the entrance length on acoustic wave generation, but channel height due to wave reflection and interference inside of the cavity has a significant impact on wave frequency and sound pressure level. Channel height has also impact on generation and shape of the vortex created in the cavity inlet.

The paper extends the knowledge of phenomena taking place in the ducted cavities. Results obtained from these investigations will be useful in designing new cooling techniques and in noise reduction. The CFD analysis makes it possible to determine the correlations between channel dimensions and SPL function and frequency of sound waves.

It is currently difficult to measure temperature and pressure in harsh environments. Such measurements are limited by either the ability of the sensing element or the associated electrical wiring to withstand the operating environment. This is unfortunate as temperature and pressure are important measurands in various engineering structures as they provide critical information on the operating condition of the structure. Hence, there is a need to address this shortcoming. Such a sensor in place would enhance the operating efficiency thereby reducing the pollution burden and its impact on the environment. The purpose of this paper is to present theoretical and preliminary experimental results for a co‐integrated pressure and temperature sensor for harsh environments.

This work describes a co‐integrated pressure‐temperature wireless sensing scheme. The approach presented herein provides the possibility of measuring dynamic pressure and temperature within an enclosed volume using acoustic signals. Resonance tube physics is exploited for the temperature sensing. A microphone is used to obtain the acoustic signal whose frequency is a function of the temperature and the tube geometry.

The dynamic pressure is measured from the calibrated amplitude of the pressure wave signal measured by the microphone. The temperature can be measured through the shift of the standing wave frequency with a resolution of <1°C. The resonance tube can be fabricated using any material that resists harsh environments. The geometry of the tube can be tailored for any specific frequency range, as the application warrants. Also, this provides a means for accurate temperature compensation of pressure sensor data from high temperature environments. A Matlab/Simulink model is developed and presented for the acquisition of acoustic signals through the wall of an enclosed volume. For these applications the standing wave signal transmitted through the enclosure wall becomes a function of the wall material and wall thickness. Preliminary experimental results are presented in which a DC fan is used for generating the dynamic pressure in a varying temperature environment.

The major issue is the separation of the noise from the signal. As various applications yield specific signal noise, the problem needs detailed data to be addressed.

Temperature and dynamic pressure could be recorded/monitored in very harsh environment conditions such as chemical reactors.

This work demonstrates the possibility of employing a co‐integrated acoustic sensing scheme in which both pressure and temperature are measured simultaneously with a sole sensor. The major advantage with acoustic sensing is the wireless transmission of data. This allows for non‐invasive measurement from within enclosed systems. Direct real‐time temperature compensation is possible that does not require any compensation circuitry. Hence, pressure and temperature data may be obtained from caustic operating environments whose access is otherwise not feasible.

This study aims to understand the influence of megasonic (MS)-assisted agitation on printed circuit boards (PCBs) electroplated using copper (Cu) electrolyte solutions to improve plating efficiencies through enhanced ion transportation.

The impact of MS-assisted agitation on topographical properties of the electroplated surfaces was studied through a design of experiments by measuring surface roughness, which is characterised by values of the parameter Ra as measured by white light phase shifting interferometry and high-resolution scanning electron microscopy.

An increase in Ra from 400 to 760 nm after plating was recorded for an increase in acoustic power from 45 to 450 W. Roughening increased because of micro-bubble cavitation energy and was supported through direct imaging of the cavitation. Current thieving effect by the MS transducer induced low currents, leading to large Cu grain frosting and reduction in the board quality. Current thieving was negated in plating trials through specific placement of transducer. Wavy electroplated surfaces, due to surface acoustic waves, were also observed to reduce the uniformity of the deposit.

The formation of unstable transient cavitation and variation of the topology of the Cu surface are unwanted phenomena. Further plating studies using MS agitation are needed, along with fundamental simulations, to determine how the effects can be reduced or prevented.

This study can help identify manufacturing settings required for high-quality MS-assisted plating and promote areas for further investigation, leading to the development of an MS plating manufacturing technique.

This study quantifies the topographical changes to a PCB surface in response to MS agitation and evidence for deposited Cu artefacts due to acoustic effects.

To develop a new method for estimation of damage configuration in composite laminate structure using acoustic wave propagation signal and a reduction‐prediction neural network to deal with high dimensional spectral data.

A reduction‐prediction network, which is a combination of an independent component analysis (ICA) and a multi‐layer perceptron (MLP) neural network, is proposed to quantify the damage state related to transverse matrix cracking in composite laminates using acoustic wave propagation model. Given the Fourier spectral response of the damaged structure under frequency band‐selective excitation, the problem is posed as a parameter estimation problem. The parameters are the stiffness degradation factors, location and approximate size of the stiffness‐degraded zone. A micro‐mechanics model based on damage evolution criteria is incorporated in a spectral finite element model (SFEM) for beam type structure to study the effect of transverse matrix crack density on the acoustic wave response. Spectral data generated by using this model is used in training and testing the network. The ICA network called as the reduction network, reduces the dimensionality of the broad‐band spectral data for training and testing and sends its output as input to the MLP network. The MLP network, in turn, predicts the damage parameters.

Numerical demonstration shows that the developed network can efficiently handle high dimensional spectral data and estimate the damage state, damage location and size accurately.

Only numerical validation based on a damage model is reported in absence of experimental data. Uncertainties during actual online health monitoring may produce errors in the network output. Fault‐tolerance issues are not attempted. The method needs to be tested using measured spectral data using multiple sensors and wide variety of damages.

The developed network and estimation methodology can be employed in practical structural monitoring system, such as for monitoring critical composite structure components in aircrafts, spacecrafts and marine vehicles.

A new method is reported in the paper, which employs the previous works of the authors on SFEM and neural network. The paper addresses the important problem of high data dimensionality, which is of significant importance from practical engineering application viewpoint.

Wireless sensor networks (WSN), as a solution for buried water pipe monitoring, face a new set of challenges compared to traditional application for above-ground infrastructure monitoring. One of the main challenges for underground WSN deployment is the limited range (less than 3 m) at which reliable wireless underground communication can be achieved using radio signal propagation through the soil. To overcome this challenge, the purpose of this paper is to investigate a new approach for wireless underground communication using acoustic signal propagation along a buried water pipe.

An acoustic communication system was developed based on the requirements of low cost (tens of pounds at most), low power supply capacity (in the order of 1 W-h) and miniature (centimetre scale) size for a wireless communication node. The developed system was further tested along a buried steel pipe in poorly graded SAND and a buried medium density polyethylene (MDPE) pipe in well graded SAND.

With predicted acoustic attenuation of 1.3 dB/m and 2.1 dB/m along the buried steel and MDPE pipes, respectively, reliable acoustic communication is possible up to 17 m for the buried steel pipe and 11 m for the buried MDPE pipe.

Although an important first step, more research is needed to validate the acoustic communication system along a wider water distribution pipe network.

This paper shows the possibility of achieving reliable wireless underground communication along a buried water pipe (especially non-metallic material ones) using low-frequency acoustic propagation along the pipe wall.

Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However, stability has been one of the key issues which have limited their effective commercial applications. To fully understand this challenge of operation stability, this paper aims to systematically review mechanisms, stability issues and future challenges of SAW sensors for various applications.

This review paper starts with different types of SAWs, advantages and disadvantages of different types of SAW sensors and then the stability issues of SAW sensors. Subsequently, recent efforts made by researchers for improving working stability of SAW sensors are reviewed. Finally, it discusses the existing challenges and future prospects of SAW sensors in the rapidly growing Internet of Things-enabled application market.

A large number of scientific articles related to SAW technologies were found, and a number of opportunities for future researchers were identified. Over the past 20 years, SAW-related research has gained a growing interest of researchers. SAW sensors have attracted more and more researchers worldwide over the years, but the research topics of SAW sensor stability only own an extremely poor percentage in the total researc topics of SAWs or SAW sensors.

Although SAW sensors have been attracting researchers worldwide for decades, researchers mainly focused on the new materials and design strategies for SAW sensors to achieve good sensitivity and selectivity, and little work can be found on the stability issues of SAW sensors, which are so important for SAW sensor industries and one of the key factors to be mature products. Therefore, this paper systematically reviewed the SAW sensors from their fundamental mechanisms to stability issues and indicated their future challenges for various applications.