scholarly journals Detection of Cracking in Gear Teeth Using Acoustic Emission

2010 ◽  
Vol 24-25 ◽  
pp. 45-50 ◽  
Author(s):  
Rhys Pullin ◽  
A. Clarke ◽  
Mark J. Eaton ◽  
Karen M. Holford ◽  
S.L. Evans ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Health Monitoring ◽  
Gear Tooth ◽  
Fatigue Loading ◽  
Image Correlation ◽  
Initial Development ◽  
Gear Teeth ◽  
Future Work ◽  
Inspection Techniques ◽  
Ae Signals

The detection of damage in gear teeth is paramount to any condition monitoring or structural health monitoring (SHM) tool for aerospace power transmissions such as those used in helicopters. Current inspection techniques include vibration analysis and time-inefficient visual inspection. Acoustic Emission (AE) is a very sensitive detection tool that has been successfully used in many SHM systems. Successful application of AE for damage detection in gear teeth will enable the optimisation of gear box design (and hence weight saving) in addition to safety improvements. This paper details a small aspect of a larger project designed to demonstrate automatic detection and location of common gear tooth defects. A novel test rig was designed to allow the fatigue loading of an individual gear tooth which was monitored using AE. The gear tooth was static in order to exclude the detection of AE signals arising from rotation; this allows initial development of the methodology prior to investigating rotating gears. Digital Image Correlation was used to determine the onset of cracking for comparison with the detected AE. Preliminary results of the investigation show that the developed methodology is appropriate for developing an automated gear health monitoring system and that future work should concentrate on the development of sensors and data acquisition methods associated with obtaining signals from rotating machinery.

Automated Damage Detection in Composite Components Using Acoustic Emission

2013 ◽  
Vol 569-570 ◽  
pp. 80-87 ◽  
Author(s):  
Rhys Pullin ◽  
Matthew R. Pearson ◽  
Mark J. Eaton ◽  
Carol A. Featherston ◽  
Karen M. Holford ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Health Monitoring ◽  
Composite Structures ◽  
Impact Damage ◽  
Turbine Blades ◽  
Fatigue Loading ◽  
Potential Method ◽  
Base Line ◽  
Wind Turbine Blades ◽  
Ae Signals

The ability of a Structural Health Monitoring (SHM) system to automatically identify damage in a composite structure is a vital requirement demanded by end-users of such systems. This paper presents the demonstration of a potential method. A composite fatigue specimen was manufactured and initially tested at 1Hz for 1000 cycles. Acoustic emission (AE) signals were recorded for complete fatigue cycles periodically in order to establish a base-line associated with undamaged specimens. The specimen was then subjected to impact damage to create barely-visible impact damage (BVID) and subjected to further fatigue cycles with acoustic emission recorded until failure. The data was subsequently analysed using a range of techniques including basic RMS signal levels and frequency-based analysis. At various stages during the test, C-scanning was used to validate the results obtained. Results demonstrated that AE is capable of detecting BVID in composite materials under fatigue loading. The proposed method has wide applicability to composite structures which are subjected to cyclic loading, such as wind turbine blades.

scholarly journals Validation of Acoustic Emission (AE) Crack Detection in Aerospace Grade Steel Using Digital Image Correlation

2010 ◽  
Vol 24-25 ◽  
pp. 221-226 ◽  
Author(s):  
Rhys Pullin ◽  
Mark J. Eaton ◽  
James J. Hensman ◽  
Karen M. Holford ◽  
Keith Worden ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Digital Image Correlation ◽  
Crack Growth ◽  
Digital Image ◽  
Crack Detection ◽  
Peak Load ◽  
Fatigue Loading ◽  
Image Correlation ◽  
Crack Mouth Opening Displacement ◽  
Ae Signals

Acoustic Emission (AE) is a passive form of non-destructive testing that relies on the detection and analysis of stress waves released during crack propagation. AE techniques are successfully employed number of industries there remains some scepticism in aerospace engineering. The reported investigation details a single four point bend test specimen undergoing fatigue loading. This test is part of a much larger programme designed to demonstrate a technology readiness level (TRL) of five of the use of AE to detect crack initiation and growth in landing gear structures. The completed test required that crack growth had to be monitored to allow a comparison with the detected and located AE signals. The method of crack monitoring had to be non-contact so as not to produce frictional sources of AE in the crack region, preventing the use of crack mouth opening displacement gauges. Furthermore adhesives on the specimen surface had to be avoided to eliminate the possibility that the detected AE was from adhesive cracking, thus the use of strain gauges or foil crack gauges was not possible. A method using Digital Image Correlation (DIC) to monitor crack growth was investigated. The test was stopped during fatigue loading at 1000 cycle intervals and a DIC image captured at peak load. The displacement due to crack growth was observed throughout the investigation and the results compared with the detected AE signals. Results showed a clear correlation between AE and crack growth and added further evidence of TRL5 for detecting fractures in landing gears using AE.

scholarly journals Optimisation of acoustic emission wavestreaming for structural health monitoring

2020 ◽  
Vol 19 (6) ◽  
pp. 2007-2022
Author(s):  
John P McCrory ◽  
Matthew R Pearson ◽  
Rhys Pullin ◽  
Karen M Holford
Keyword(s):  
Acoustic Emission ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Peak Frequency ◽  
Image Correlation ◽  
The Novel ◽  
Structural Health ◽  
Growth Activity ◽  
Materials Used ◽  
Novel Concept

Structural health monitoring has gained wide appeal for applications with high inspection costs, such as aircraft and wind turbines. As the structures and materials used in these industries evolve, so too must the technologies used to monitor them. Acoustic emission is a passive method of detecting damage which lends itself well to structural health monitoring. One form of acoustic emission monitoring, known as wavestreaming, involves intermittently recording data for set periods of time and using the sequential recordings to detect changes in the state of the structure. However, at present, there is no standard method for selecting appropriate wavestream recording parameters, such as their length or their interval of collection. This article investigates a method of optimising acoustic emission wavestreaming for structural health monitoring purposes by introducing the novel concept of adjoining consecutive discrete acoustic emission hit signals to create synthetic wavestreams. To this end, a pre-notched 492 mm × 67.5 mm × 20 mm, 300M grade steel cantilever specimen was subject to cyclic loading and both acoustic emission hit data and conventional wavestreams were collected as a crack grew in the notched region; crack growth activity was also monitored using digital image correlation for comparison. To demonstrate the proposed optimisation process, four sets of synthetic wavestreams were created from the hit data, 0.25, 0.5, 1.0 and 1.5 s in length, and compared with the 1.5-s-long conventional wavestreams. The activity of the peak frequency and frequency centroid bands of interest within the conventional and synthetic wavestreams were examined to determine whether or not cracking activity could be inferred through them. Across comparisons of all data, it was found that the 0.5-s-long synthetic wavestreams contained enough information to identify the same trends as the conventional wavestreams for this application; thus, the use of synthetic wavestreams as a tool for selecting an appropriate wavestream recording length was demonstrated.

scholarly journals Identification of Fatigue Damage Stages in Polymer Composite Materials by using Acoustic Emission: Approach and Perspectives

2021 ◽  
Author(s):  
Oleg Bashkov ◽  
Anton Bryansky ◽  
Timofey Efimov ◽  
Roman Romashko
Keyword(s):  
Acoustic Emission ◽  
Composite Material ◽  
Polymer Composite ◽  
Fatigue Loading ◽  
Polymer Composite Material ◽  
Self Organizing Map ◽  
Local Formation ◽  
Adhesion Failure ◽  
The Matrix ◽  
Ae Signals

The work is devoted to the study of the mechanisms of damage accumulation in a polymer composite material (PCM) during fatigue loading. Mechanical testing of a fiberglass sample was carried out by cyclic tension accompanied by registration of acoustic emission (AE). For the recorded AE signals, the Fourier spectra were calculated and used for clustering with Kohonen self-organizing map. Relations between clusters and types of damage in the PCM structure were established. The analysis of the peak frequencies of the Daubechies D14-wavelet components of AE signals was carried out. Obtained results has allows one to describe the processes of destruction in the PCM sample. It has been established that, on the base of local formation of microdamages in the matrix and the fracture of the fibers detected during recording of the AE data, it is possible to predict the destruction of the polymer composite material, while the beginning of a material destruction can be registered if the damage identified as an adhesion failure is observed. Perspectives of application of adaptive fiber-optic AE sensors for structural monitoring of PCMs on the base of preliminary experimental results are considered and discussed.

scholarly journals Quantification of Gear Tooth Damage by Optimal Tracking of Vibration Signatures

1997 ◽  
Vol 3 (3) ◽  
pp. 143-151 ◽  
Author(s):  
F. K. Choy ◽  
R. J. Veillette ◽  
V. Polyshchuk ◽  
M. J. Braun ◽  
R. C. Hendricks
Keyword(s):  
Monitoring System ◽  
Health Monitoring ◽  
Gear Tooth ◽  
Operating Conditions ◽  
Diagnostic Process ◽  
Data Set ◽  
Health Monitoring System ◽  
Gear Teeth ◽  
Gear Mesh ◽  
Machine Health Monitoring

This paper presents a technique for quantifying the wear or damage of gear teeth in a transmission system. The procedure developed in this study can be applied as a part of either an onboard machine health-monitoring system or a health diagnostic system used during regular maintenance. As the developed methodology is based on analysis of gearbox vibration under normal operating conditions, no shutdown or special modification of operating parameters is required during the diagnostic process.The process of quantifying the wear or damage of gear teeth requires a set of measured vibration data and a model of the gear mesh dynamics. An optimization problem is formulated to determine the profile of a time-varying mesh stiffness parameter for which the model output approximates the measured data. The resulting stiffness profile is then related to the level of gear tooth wear or damage.The procedure was applied to a data set generated artificially and to another obtained experimentally from a spiral bevel gear test rig. The results demonstrate the utility of the procedure as part of an overall health-monitoring system.

scholarly journals Impact Damage Ascertainment in Composite Plates Using In-Situ Acoustic Emission Signal Signature Identification

2021 ◽  
Vol 5 (3) ◽  
pp. 79
Author(s):  
Robin James ◽  
Roshan Prakash Joseph ◽  
Victor Giurgiutiu
Keyword(s):  
Acoustic Emission ◽  
Health Monitoring ◽  
Impact Damage ◽  
Impact Event ◽  
Internal Damage ◽  
Emission Signal ◽  
Monitoring Technique ◽  
The Impact ◽  
Impact Events ◽  
Ae Signals

Barely visible impact damage (BVID) due to low velocity impact events in composite aircraft structures are becoming prevalent. BVID can have an adverse effect on the strength and safety of the structure. During aircraft inspections it can be extremely difficult to visually detect BVID. Moreover, it is also a challenge to ascertain if the BVID has in-fact caused internal damage to the structure or not. This paper describes a method to ascertain whether or not internal damage happened during the impact event by analyzing the high-frequency information contained in the recorded acoustic emission signal signature. Multiple 2 mm quasi-isotropic carbon fiber reinforced polymer (CFRP) composite coupons were impacted using the ASTM D7136 standard in a drop weight impact testing machine to determine the mass, height and energy parameters to obtain approximately 1” impact damage size in the coupons iteratively. For subsequent impact tests, four piezoelectric wafer active sensors (PWAS) were bonded at specific locations on each coupon to record the acoustic emission (AE) signals during the impact event using the MISTRAS micro-II digital AE system. Impact tests were conducted on these instrumented 2 mm coupons using previously calculated energies that would create either no damage or 1” impact damage in the coupons. The obtained AE waveforms and their frequency spectrums were analyzed to distinguish between different AE signatures. From the analysis of the recorded AE signals, it was verified if the structure had indeed been damaged due to the impact event or not. Using our proposed structural health monitoring technique, it could be possible to rapidly identify impact events that cause damage to the structure in real-time and distinguish them from impact events that do not cause damage to the structure. An invention disclosure describing our acoustic emission structural health monitoring technique has been filed and is in the process of becoming a provisional patent.

scholarly journals Identification of acoustic emission sources under cyclic loading of the polymer composite material used in shipbuilding

2021 ◽  
pp. 28-33
Author(s):  
О.В. Башков ◽  
А.А. Брянский ◽  
Т.И. Башкова
Keyword(s):  
Acoustic Emission ◽  
Composite Material ◽  
Polymer Composite ◽  
Mechanical Test ◽  
Fatigue Loading ◽  
Polymer Composite Material ◽  
Second Stage ◽  
Kohonen Map ◽  
Ae Signals ◽  
Critical Intensity

Данная работа посвящена исследованию механизмов накопления повреждений в полимерном композиционном материале (ПКМ) в ходе усталостного нагружения. Механическое испытание образца стеклопластика проводили циклическим растяжением в сопровождении регистрации акустической эмиссии (АЭ). Для зарегистрированных сигналов АЭ рассчитывались спектры Фурье и использовались для кластеризации самоорганизующейся картой Кохонена (SOM). Полученные центроиды, для снижения количества анализируемых кластеров, разделяли на кластеры методом k-средних. Кластеры второго этапа кластеризации соотносились с типами повреждений в структуре ПКМ. Рассчитывались периоды критической интенсивности регистрации различных типов образующихся повреждений. Дополнительно проведён анализ пиковых частот уровней вейвлет декомпозиции Добеши 14 сигналов АЭ. На основании проведенных методов анализа данных АЭ описаны протекающие процессы разрушения в образце ПКМ. This work is aimed the study the mechanisms of damage accumulation in a polymer composite material (PCM) during fatigue loading. Mechanical test of a fiberglass sample was done by cyclic tension with acoustic emission (AE) registration. The Fourier spectra were calculated for the recorded AE signals and used for clustering with a self-organizing Kohonen map (SOM). The obtained centroids, in order to reduce the number of analyzed clusters, were divided into clusters by the k-means method. Clusters of the second stage clustering correlated with the types of damage in the structure of the PCM. The periods of the critical intensity of registration of various types of formed damages were calculated. Additionally, the peak frequencies of the levels of Daubechies 14 wavelet decomposition of AE signals was analyzed. Based on the methods for analyzing the AE data, the processes of destruction in the PCM sample are described.

An acoustic emission-based approach to structural health monitoring of pre-stressed concrete railway sleepers

2020 ◽  
Vol 62 (5) ◽  
pp. 280-291
Author(s):  
M Carboni ◽  
A Collina ◽  
E Zappa
Keyword(s):  
Acoustic Emission ◽  
Structural Health Monitoring ◽  
Monitoring System ◽  
Health Monitoring ◽  
Structural Integrity ◽  
Essential Element ◽  
Image Correlation ◽  
Damage Development ◽  
Safety Issues ◽  
Structural Health

Railway sleepers represent an essential element of the track; indeed, their structural integrity is closely related to important technical and safety issues. Today, periodical visual inspections are the only method applied to check the status of sleepers but are limited to visible surfaces, whereas the early detection of in-service cracks in the whole volume of sleepers would provide great advantages in terms of maintenance and management. The aim of the paper is to propose an acoustic emission (AE)-based structural health monitoring (SHM) approach that is able to detect the initiation and propagation of cracks in in-service pre-stressed concrete sleepers. The investigation is carried out in the laboratory, comparing the results obtained by acoustic emission monitoring and digital image correlation when subjecting pre-stressed concrete sleepers, taken from production, to both static and cyclic loads. The main points dealt with in the paper include the sensitivity of acoustic emission to detect damage development and the signal processing approach needed for defining effective damage indexes. Given the encouraging results, the paper is the first step in developing an affordable monitoring system, to be embedded into sleepers, that is able to be part of a complete track monitoring system.

Pre-failure indicators detected by Acoustic Emission: Alfas stone, cement-mortar and cement-paste specimens under 3-point bending

2018 ◽  
Vol 11 (40) ◽  
pp. 74-84
Author(s):  
Stavros K. Kourkoulis ◽  
Ioanna Dakanali
Keyword(s):  
Acoustic Emission ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Cement Mortar ◽  
Clear Understanding ◽  
Stone Monuments ◽  
Good Accordance ◽  
Structural Tests ◽  
Ae Signals

Acoustic Emission (AE) is the technique most widely used nowadays for Structural Health Monitoring (SHM). Application of this technique for continuous SHM of restored elements of stone monuments is a challenging task. The co-existence of different materials creates interfaces rendering “identification” of the signals recorded very complicated. To overcome this difficulty one should have a clear overview of the nature of AE signals recorded when each one of the constituent materials is loaded mechanically. In this direction, an attempt is here described to enlighten the signals recorded, in case a series of structural materials (natural and artificial), extensively used for restoration projects of classic monuments in Greece, are subjected to 3-point bending. It is hoped that obtaining a clear understanding of the nature of AE signals recorded during these elementary tests will provide a valuable tool permitting “identification” and “classification” of signals emitted in case of structural tests. The results appear encouraging. In addition, it is concluded that for all materials tested (in spite their differences in microstructure and composition) clear prefailure indicators are detected, in good accordance to similar indicators provided by other techniques like the Pressure Stimulated Currents (PSC) one.

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