Experimental Study of the Earthquake Recurrence Period and the Trend of Post-Seismic Development

In order to study the earthquake recurrence and the characteristics of earthquake series, rupture tests of rock samples and plexiglass samples were made. On rock samples, a number of acoustic emission (AE) and strain measuring points were deployed; the load was one side direct shear. The variation characteristics of AE and strain at different detecting points around the extra large fracture were observed and studied. On plexiglass samples, a series of inclined cracks were prefabricated by a small-scale compressive testing machine. The samples were then loaded on a shockproof platen, when the samples were loaded, the stress intensity factor (SIF) was determined by the laser interferometric technique and shadow optical method of caustics. The fracture conditions such as material toughness around the extra large fracture were also studied. From those experimental results and the theory of fracture mechanics, the earthquake recurrence period and the trend of post-seismic development were studied.

Static and fatigue failure behavior of carbon-fiber reinforced epoxy composite-materials with edge notch

A study of carbon fiber reinforced epoxy composite material with 0° ply or ±45°ply(unnotched or with edge notch) was carried out under static tensile and tension-tensioncyclic loading testing. Static and fatigue behaviour and damage failure modes in unnotched/notched specimens plied in different manners were analysed and compared with each other.A variety of techniques (acoustic emission, two types of strain extensometer, high speed pho-tography, optical microscopy, scanning electron microscope, etc.) were used to examine thedamage of the laminates. Experimental results show that when these carbon/epoxy laminateswith edge notch normal to the direction of the load are axially loaded in static or fatiguetension, the crack does not propagate along the length of notch but is in the interface (fiberdirection). The notch has no substantial effect on the stresses at the unnotched portion. Thedamage failure mechanism is discussed.

Acoustic condition monitoring for cold metal forming

One of the most important objectives of cold metal forming research is to develop techniques that enable better manufacturing efficiencies. Within this monitoring of tooling condition is vital to providing high quality manufacturing. The objective of this research is to determine the signature derived from Acoustic Emission (AE) sensors, in order to establish the current condition of a machine tool, as applied to bolt-making. From here we aim to develop and implement an on-line condition monitoring tool for the cold forming process. A review of the literature has shown that much research into AE has been successfully applied in metal cutting operations; such as milling, drilling and turning, but little research has been done related to metal forming. This appears to be due to the complexity of obtaining consistent signals using Acoustic Emission systems, because the presence of noise in many forms. This paper will detail many of the AE signals acquired and analysed through our research. The extensive results indicate this form of condition monitoring is not suitable for metal forming in its current configuration. Further tests are proposed to enable such research to move forward, so a condition monitoring system can be established.

Efeitos da granulometria, do desgaste e do tipo de material abrasivo no lixamento plano de madeiras

Pós-graduação em Engenharia Mecânica - FEG

Ultrasonic acoustic emissions in drought-stressed trees - more than signals from cavitation?

Ultrasonic acoustic emission (UAE) in trees is often related to collapsing water columns in the flow path as a result of tensions that are too strong (cavitation). However, in a decibel (dB) range below that associated with cavitation, a close relationship was found between UAE intensities and stem radius changes. • UAE was continuously recorded on the stems of mature field-grown trees of Scots pine (Pinus sylvestris) and pubescent oak (Quercus pubescens) at a dry inner-Alpine site in Switzerland over two seasons. The averaged 20-Hz records were related to microclimatic conditions in air and soil, sap-flow rates and stem-radius fluctuations de-trended for growth (ΔW). • Within a low-dB range (27 ± 1 dB), UAE regularly increased and decreased in a diurnal rhythm in parallel with ΔW on cloudy days and at night. These low-dB emissions were interrupted by UAE abruptly switching between the low-dB range and a high-dB range (36 ± 1 dB) on clear, sunny days, corresponding to the widely supported interpretation of UAE as sound from cavitations. • It is hypothesized that the low-dB signals in drought-stressed trees are caused by respiration and/or cambial growth as these physiological activities are tissue water-content dependent and have been shown to produce courses of CO2 efflux similar to our courses of ΔW and low-dB UAE.

Discrimination of AE Signals From Friction and Concrete Cracking in a Reinforced Concrete Frame Subjected to Seismic Trainings

This paper shows the preliminary results of the development and application of a procedure to filter the Acoustic Emission (AE) signals to distinguish between AE signals coming from friction and AE signals coming from concrete cracking. These signals were recorded during the trainings of an experiment carried out on a reinforced concrete frame subjected to dynamic loadings with the shaking table of the University of Granada (Spain). Discrimination between friction and cracking AE signals is the base to develop a successful procedure and damage index based on AE testing for health monitoring of RC structures subjected to earthquakes.

Modified Gutenberg-Richter coefficient for damage evaluation in reinforced concrete structures subjected to seismic simulations on a shaking table

This paper presents analysis and discussion of the b- and ib-values calculated from the acoustic emission (AE) signals recorded during dynamic shake-table tests conducted on a reinforced concrete (RC) frame subjected to several uniaxial seismic simulations of increasing intensity until collapse. The intensity of shaking was controlled by the peak acceleration applied to the shake-table in each seismic simulation, and it ranged from 0.08 to 0.47 times the acceleration of gravity. The numerous spurious signals not related to concrete damage that inevitably contaminate AE measurements obtained from complex dynamic shake-table tests were properly filtered with an RMS filter and the use of guard sensors. Comparing the b- and ib-values calculated through the tests with the actual level of macro-cracking and damage observed during testing, it was concluded that the limit value of 0.05 proposed in previous research to determine the onset of macro-cracks should be revised in the case of earthquake-type dynamic loading. Finally, the b- and ibvalues were compared with the damage endured by the RC frame evaluated both visually and quantitatively in terms of the inter-story drift index.

Damage assessment in structures using vibration characteristics

Changes in load characteristics, deterioration with age, environmental influences and random actions may cause local or global damage in structures, especially in bridges, which are designed for long life spans. Continuous health monitoring of structures will enable the early identification of distress and allow appropriate retrofitting in order to avoid failure or collapse of the structures. In recent times, structural health monitoring (SHM) has attracted much attention in both research and development. Local and global methods of damage assessment using the monitored information are an integral part of SHM techniques. In the local case, the assessment of the state of a structure is done either by direct visual inspection or using experimental techniques such as acoustic emission, ultrasonic, magnetic particle inspection, radiography and eddy current. A characteristic of all these techniques is that their application requires a prior localization of the damaged zones. The limitations of the local methodologies can be overcome by using vibration-based methods, which give a global damage assessment. The vibration-based damage detection methods use measured changes in dynamic characteristics to evaluate changes in physical properties that may indicate structural damage or degradation. The basic idea is that modal parameters (notably frequencies, mode shapes, and modal damping) are functions of the physical properties of the structure (mass, damping, and stiffness). Changes in the physical properties will therefore cause changes in the modal properties. Any reduction in structural stiffness and increase in damping in the structure may indicate structural damage. This research uses the variations in vibration parameters to develop a multi-criteria method for damage assessment. It incorporates the changes in natural frequencies, modal flexibility and modal strain energy to locate damage in the main load bearing elements in bridge structures such as beams, slabs and trusses and simple bridges involving these elements. Dynamic computer simulation techniques are used to develop and apply the multi-criteria procedure under different damage scenarios. The effectiveness of the procedure is demonstrated through numerical examples. Results show that the proposed method incorporating modal flexibility and modal strain energy changes is competent in damage assessment in the structures treated herein.

Diesel engine condition monitoring and simulated diesel knock

This paper discusses diesel engine condition monitoring (CM) using acoustic emissions (AE) as well as some of the commonly encountered diesel engine problems. Also discussed are some of the underlying combustion related faults and the methods used in past studies to simulate diesel engine faults. The initial test involved an experimental simulation of two common combustion related diesel engine faults, namely diesel knock and misfire. These simulated faults represent the first step towards a comprehensive investigation and analysis into the characteristics of acoustic emission signals arising from combustion related diesel engine faults. Data corresponding to different engine running conditions was captured using in-cylinder pressure, vibration and acoustic emission transducers along with both crank angle encoder and top-dead centre (TDC) signals. Using these signals, it was possible to characterise the effect of different combustion conditions and hence, various diesel engine in-cylinder pressure profiles.

Development of an online condition monitoring system for slow speed machinery

One of the main challenges of slow speed machinery condition monitoring is that the energy generated from an incipient defect is too weak to be detected by traditional vibration measurements due to its low impact energy. Acoustic emission (AE) measurement is an alternative for this as it has the ability to detect crack initiations or rubbing between moving surfaces. However, AE measurement requires high sampling frequency and consequently huge amount of data are obtained to be processed. It also requires expensive hardware to capture those data, storage and involves signal processing techniques to retrieve valuable information on the state of the machine. AE signal has been utilised for early detection of defects in bearings and gears. This paper presents an online condition monitoring (CM) system for slow speed machinery, which attempts to overcome those challenges. The system incorporates relevant signal processing techniques for slow speed CM which include noise removal techniques to enhance the signal-to-noise and peak-holding down sampling to reduce the burden of massive data handling. The analysis software works under Labview environment, which enables online remote control of data acquisition, real-time analysis, offline analysis and diagnostic trending. The system has been fully implemented on a site machine and contributing significantly to improve the maintenance efficiency and provide a safer and reliable operation.

Diesel engine condition monitoring and simulated diesel knock

This paper discusses diesel engine condition monitoring (CM) using acoustic emissions (AE)as well as some of the commonly encountered diesel engine problems. Also discussed are some of the underlying combustion related faults and the methods used in past studies to simulate diesel engine faults. The initial test involved an experimental simulation of two common combustion related diesel engine faults, namely diesel knock and misfire. These simulated faults represent the first step towards a comprehensive investigation and analysis into the characteristics of acoustic emission signals arising from combustion related diesel engine faults. Data corresponding to different engine running conditions was captured using in-cylinder pressure, vibration and acoustic emission transducers along with both crank angle encoder and top-dead centre (TDC) signals. Using these signals, it was possible to characterise the effect of different combustion conditions and hence, various diesel engine in-cylinder pressure profiles.

Development of a diagnostic tool for condition monitoring of rotating machinery

This paper presents an overview of the CRC for Infrastructure and Engineering Asset Management (CIEAM)’s rotating machine health monitoring project and the status of the research progress. The project focuses on the development of a comprehensive diagnostic tool for condition monitoring and systematic analysis of rotating machinery. Particularly attention focuses on the machine health monitoring of diesel engines, compressors and pumps by using acoustic emission and vibration-based monitoring techniques. The paper also provides a brief summary of the work done by the three main research collaborating partners in the project, namely, Queensland University of Technology (QUT), Curtin University of Technology (CUT) and the University of Western Australia (UWA). Preliminary test and analysis results from this work are also reported in the paper

A practical signal processing approach for condition monitoring of low speed machinery using Peak-Hold-Down-Sample algorithm

A simple and effective down-sample algorithm, Peak-Hold-Down-Sample (PHDS) algorithm is developed in this paper to enable a rapid and efficient data transfer in remote condition monitoring applications. The algorithm is particularly useful for high frequency Condition Monitoring (CM) techniques, and for low speed machine applications since the combination of the high sampling frequency and low rotating speed will generally lead to large unwieldy data size. The effectiveness of the algorithm was evaluated and tested on four sets of data in the study. One set of the data was extracted from the condition monitoring signal of a practical industry application. Another set of data was acquired from a low speed machine test rig in the laboratory. The other two sets of data were computer simulated bearing defect signals having either a single or multiple bearing defects. The results disclose that the PHDS algorithm can substantially reduce the size of data while preserving the critical bearing defect information for all the data sets used in this work even when a large down-sample ratio was used (i.e., 500 times down-sampled). In contrast, the down-sample process using existing normal down-sample technique in signal processing eliminates the useful and critical information such as bearing defect frequencies in a signal when the same down-sample ratio was employed. Noise and artificial frequency components were also induced by the normal down-sample technique, thus limits its usefulness for machine condition monitoring applications.