Study of acoustic emission data analysis tools for structural health monitoring applications

Acoustic emission (AE) technique is one of the popular diagnostic techniques used for structural health monitoring of mechanical, aerospace and civil structures. But several challenges still exist in successful application of AE technique. This paper explores various tools for analysis of recorded AE data to address two primary challenges: discriminating spurious signals from genuine signals and devising ways to quantify damage levels.

Structural health monitoring of bridges : source localisation in acoustic emission technique

Managing the sustainability of urban infrastructure requires regular health monitoring of key infrastructure such as bridges. The process of structural health monitoring involves monitoring a structure over a period of time using appropriate sensors, extracting damage sensitive features from the measurements made by the sensors, and analysing these features to determine the current state of the structure. Various techniques are available for structural health monitoring of structures, and acoustic emission is one technique that is finding an increasing use in the monitoring of civil infrastructures such as bridges. Acoustic emission technique is based on the recording of stress waves generated by rapid release of energy inside a material, followed by analysis of recorded signals to locate and identify the source of emission and assess its severity. This chapter first provides a brief background of the acoustic emission technique and the process of source localization. Results from laboratory experiments conducted to explore several aspects of the source localization process are also presented. The findings from the study can be expected to enhance knowledge of the acoustic emission process, and to aid the development of effective bridge structure diagnostics systems.

Enhancing acoustic emission signals from multi-cylinder diesel engine

This paper presents techniques which can be viewed as pre-processing step towards diagnosis of faults in a small size multi-cylinder diesel engine. Preliminary analysis of the acoustic emission (AE) signals is outlined, including time-frequency analysis, selection of optimum frequency band. Some results of applying mean field independent component analysis (MFICA) to separate the AE root mean square (RMS) signals are also outlined. The results on separation of RMS signals show this technique has the potential of increasing the probability to successfully identify the AE events associated with the various mechanical events.

Analysis of acoustic emission data for structural health monitoring applications

Acoustic emission (AE) is the phenomenon where high frequency stress waves are generated by rapid release of energy within a material by sources such as crack initiation or growth. AE technique involves recording these stress waves by means of sensors placed on the surface and subsequent analysis of the recorded signals to gather information such as the nature and location of the source. It is one of the several diagnostic techniques currently used for structural health monitoring (SHM) of civil infrastructure such as bridges. Some of its advantages include ability to provide continuous in-situ monitoring and high sensitivity to crack activity. But several challenges still exist. Due to high sampling rate required for data capture, large amount of data is generated during AE testing. This is further complicated by the presence of a number of spurious sources that can produce AE signals which can then mask desired signals. Hence, an effective data analysis strategy is needed to achieve source discrimination. This also becomes important for long term monitoring applications in order to avoid massive date overload. Analysis of frequency contents of recorded AE signals together with the use of pattern recognition algorithms are some of the advanced and promising data analysis approaches for source discrimination. This paper explores the use of various signal processing tools for analysis of experimental data, with an overall aim of finding an improved method for source identification and discrimination, with particular focus on monitoring of steel bridges.

Application of acoustic emission technology in monitoring structure integrity of bridges

Bridges are an important part of a nation’s infrastructure and reliable monitoring methods are necessary to ensure their safety and efficiency. Most bridges in use today were built decades ago and are now subjected to changes in load patterns that can cause localized distress, which can result in bridge failure if not corrected. Early detection of damage helps in prolonging lives of bridges and preventing catastrophic failures. This paper briefly reviews the various technologies currently used in health monitoring of bridge structures and in particular discusses the application and challenges of acoustic emission (AE) technology. Some of the results from laboratory experiments on a bridge model are also presented. The main objectives of these experiments are source localisation and assessment. The findings of the study can be expected to enhance the knowledge of acoustic emission process and thereby aid in the development of an effective bridge structure diagnostics system.

Near infrared for non-destructive testing of articular cartilage

The concept of non-destructive testing (NDT) of materials and structures is of immense importance in engineering and medicine. Several NDT methods including electromagnetic (EM)-based e.g. X-ray and Infrared; ultrasound; and S-waves have been proposed for medical applications. This paper evaluates the viability of near infrared (NIR) spectroscopy, an EM method for rapid non-destructive evaluation of articular cartilage. Specifically, we tested the hypothesis that there is a correlation between the NIR spectrum and the physical and mechanical characteristics of articular cartilage such as thickness, stress and stiffness. Intact, visually normal cartilage-on-bone plugs from 2-3yr old bovine patellae were exposed to NIR light from a diffuse reflectance fibre-optic probe and tested mechanically to obtain their thickness, stress, and stiffness. Multivariate statistical analysis-based predictive models relating articular cartilage NIR spectra to these characterising parameters were developed. Our results show that there is a varying degree of correlation between the different parameters and the NIR spectra of the samples with R2 varying between 65 and 93%. We therefore conclude that NIR can be used to determine, nondestructively, the physical and functional characteristics of articular cartilage.

Structure of selected basic zinc/copper (II) phosphate minerals based upon near-infrared spectroscopy : implications for hydrogen bonding

The NIR spectra of reichenbachite, scholzite and parascholzite have been studied at 298 K. The spectra of the minerals are different, in line with composition and crystal structural variations. Cation substitution effects are significant in their electronic spectra and three distinctly different electronic transition bands are observed in the near-infrared spectra at high wavenumbers in the 12000-7600 cm-1 spectral region. Reichenbachite electronic spectrum is characterised by Cu(II) transition bands at 9755 and 7520 cm-1. A broad spectral feature observed for ferrous ion in the 12000-9000 cm-1 region both in scholzite and parascholzite. Some what similarities in the vibrational spectra of the three phosphate minerals are observed particularly in the OH stretching region. The observation of strong band at 5090 cm-1 indicates strong hydrogen bonding in the structure of the dimorphs, scholzite and parascholzite. The three phosphates exhibit overlapping bands in the 4800-4000 cm-1 region resulting from the combinations of vibrational modes of (PO4)3- units.

A Near-infrared and Raman spectroscopic study of the mineral richelsdorfite Ca2Cu5Sb[Cl|(OH)6|(AsO4)4]•6H2O

Raman spectroscopy has enabled insights into the molecular structure of the richelsdorfite Ca2Cu5Sb[Cl|(OH)6|(AsO4)4]·6H2O. This mineral is based upon the incorporation of arsenate or phosphate with chloride anion into the structure and as a consequence the spectra reflect the bands attributable to these anions, namely arsenate or phosphate and chloride. The richelsdorfite Raman spectrum reflects the spectrum of the arsenate anion and consists of ν1 at 849, ν2 at 344 cm−1, ν3 at 835 and ν4 at 546 and 498 cm−1. A band at 268 cm−1 is attributed to CuO stretching vibration. Low wavenumber bands at 185 and 144 cm−1 may be assigned to CuCl TO/LO optic vibrations.

A Raman and infrared spectroscopic study of the mineral delvauxite CaFe3+4(PO4,SO4)2(OH)8•4-6H2O- a ‘colloidal’ mineral

The mineral delvauxite CaFe3+4(PO4,SO4)2(OH)8•4-6H2O has been characterised by Raman spectroscopy and infrared spectroscopy. The mineral is associated with the minerals diadochite and destinezite. Delvauxite appears to vary in crystallinity from amorphous to semi-crystalline. The mineral is often X-ray non-diffracting. The minerals are found in soils and may be described as ‘colloidal’ minerals. Vibrational spectroscopy enables determination of the molecular structure of delvauxite. Bands are assigned to phosphate and sulphate stretching and bending modes. Two symmetric stretching modes for both the phosphate and sulphate symmetric stretching modes support the concept of non-equivalent phosphate and sulphate units in the mineral structure. Multiple water bending and stretching modes imply that non-equivalent water molecules in the structure exist with different hydrogen bond strengths.

Use of acoustic emission technique for structural health monitoring of bridges

Bridges are valuable assets of every nation. They deteriorate with age and often are subjected to additional loads or different load patterns than originally designed for. These changes in loads can cause localized distress and may result in bridge failure if not corrected in time. Early detection of damage and appropriate retrofitting will aid in preventing bridge failures. Large amounts of money are spent in bridge maintenance all around the world. A need exists for a reliable technology capable of monitoring the structural health of bridges, thereby ensuring they operate safely and efficiently during the whole intended lives. Monitoring of bridges has been traditionally done by means of visual inspection. Visual inspection alone is not capable of locating and identifying all signs of damage, hence a variety of structural health monitoring (SHM) techniques is used regularly nowadays to monitor performance and to assess condition of bridges for early damage detection. Acoustic emission (AE) is one technique that is finding an increasing use in SHM applications of bridges all around the world. The chapter starts with a brief introduction to structural health monitoring and techniques commonly used for monitoring purposes. Acoustic emission technique, wave nature of AE phenomenon, previous applications and limitations and challenges in the use as a SHM technique are also discussed. Scope of the project and work carried out will be explained, followed by some recommendations of work planned in future.

Molecular structure of Mg-Al, Mn-Al and Zn-Al halotrichites : an infrared spectroscopic study

Near infrared (NIR), X-ray diffraction (XRD) and infrared (IR) spectroscopy have been applied to halotrichites of the formula MgAl2(SO4)4∙22H2O, MnAl2(SO4)4∙22H2O and ZnAl2(SO4)4∙22H2O. Comparison of the halotrichites in different spectral regions has shown that the incorporation of a divalent transition metal into the halotrichite structure causes a shift in OH stretching band positions to lower wavenumbers. Therefore, an increase in hydrogen bonded water is observed for divalent cations with a larger molecular mass. XRD has confirmed the formation of halotrichite for all three samples and characteristic peaks of halotrichite have been identified at 18.5 and 24.5° 2θ, along with a group of six peaks between 5 and 15° 2θ. It has been observed that Mg-Al and Mn-Al halotrichite are very similar in structure, while Zn-Al showed several differences particularly in the NIR spectra. This work has shown that halotrichite structures can be synthesised and characterised by infrared and NIR spectroscopy.

Ultrafast near infrared sintering of TiO2 layers on metal substrates for dye-sensitized solar cells

A limiting step to roll-to-roll production of dye-sensitized solar cells on metals is TiO2 sintering (10-30 min). Near infrared (NIR) heating is a novel process innovation which directly heats titanium substrates giving rapid binder removal and sintering. NIR heating (for 12.5 s) at varying power gave titanium temperatures of 545, 685 and 817 degrees Celsius yielding cells with efficiencies of 2.9, 2.8 and 2.5%. Identical cells prepared in a conventional oven (1800 s) at 500, 600 and 800 degrees Celsius gave 2.9, 2.6 and 0.2% efficiency. NIR sintering is ultrafast and has a wide process window making it ideal for rapid manufacturing on metals.

Infrared spectroscopic study of halloysite-potassium acetate intercalation complex

Mid-infrared (MIR) and near-infrared (NIR) spectroscopy have been used to study the molecular structure of halloysite and potassium acetate intercalated halloysite and to determine the structural changes of halloysite through intercalation. The MIR spectra show all fundamental vibrations including the hydroxyl units, basic aluminosilicate framework and water molecules in the structure of halloysite and its intercalation complex. Comparison between halloysite and halloysite-potassium acetate intercalation complex shows almost all bands observed for halloysite are also observed for halloysite-potassium acetate intercalation complex apart from bands observed in the 1700-1300 cm-1 region, but with differences in band intensity. However, NIR, based on MIR spectra, provide sufficient evidence to analyze the structural changes of halloysite through intercalation. There are obvious differences between halloysite and halloysite-potassium acetate intercalation complex in the all spectral ranges. Therefore, the reproducibility of measurement and richness of qualitative information should be simultaneously considered for proper selection of a spectroscopic method for molecular structural analysis.

A raman and infrared spectroscopic study of Ca2+ dominant members of the mixite group from the Czech Republic

Raman microscopy of two mixite minerals BiCu6(AsO4)3(OH)6.3H2O from Jáchymov and from Smrkovec (both Czech Republic) has been used to study their molecular structure, which is interpreted and the presence of (AsO4)3-, (AsO3OH)2-, (PO4)3- and (PO3OH)2- units, molecular water and hydroxyl ions were inferred. O-H…O hydrogen bond lengths were calculated from the Raman and infrared spectra using Libowitzky’s empirical relation. Small differences in the Raman spectra between both samples were observed and attributed to compositional and hydrogen bonding network differences.

Near infrared spectroscopy of the smithsonite minerals

The importance of NIR spectroscopy has been successfully demonstrated in the present study of smithsonite minerals. The fundamental observations in the NIR spectra, in addition to the anions of OH- and CO32- are Fe and Cu in terms of cation content. These ions exhibit broad absorption bands ranging from 13000 to 7000cm-1 (0.77 to 1.43 µm). One broad diagnostic absorption feature centred at 9000 cm-1 (1.11 µm) is the result of ferrous ion spin allowed transition, (5T2g ® 5Eg). The splitting of this band (>1200 cm-1) is a common feature in all the spectra of the studied samples. The light green coloured sample from Namibia show two Cu(II) bands in NIR at 8050 and 10310 cm-1 (1.24 and 0.97 µm) are assigned to 2B1g ® 2A1g and 2B1g ® 2B2g transitions. The effects of structural cations substitution (Ca2+, Fe2+, Cu2+, Cd2+ and Zn2+) on band shifts in the electronic spectra1 region of 11000-7500 cm-1 (0.91-1.33 µm) and vibrational modes of OH- and CO32- anions in 7300 to 4000 cm-1 (1.37-2.50 µm) region were used to distinguish between the smithsonites.