logging in or signing up Muravin - Structural Health Monitoring using AE method - 2010 aSGuest76056 Download Post to : URL : Related Presentations : Let's Connect Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Copy embed code: Embed: Flash iPad Dynamic Copy Does not support media & animations Automatically changes to Flash or non-Flash embed WordPress Embed Customize Embed URL: Copy Thumbnail: Copy The presentation is successfully added In Your Favorites. Views: 235 Category: Science & Tech.. License: All Rights Reserved Like it (0) Dislike it (0) Added: November 21, 2010 This Presentation is Public Favorites: 1 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript Slide 1: The Fundamentals of Structural Health Monitoring using Acoustic Emission Method Dr. Boris Muravin, Prof. Gregory Muravin, Dr. Ludmila Lezvinsky Refer to: B. Muravin, G. Muravin, L. Lezvinsky, "The Fundamentals of Structural Health Monitoring by the Acoustic Emission Method", Proceedings of the 20th International Acoustic Emission Symposium, November 17-19, Kumamoto, Japan, pp. 253-258. More at: www.muravin.com The Goal of This Work : The Goal of This Work The goal of this work is development a standard approach for new AE SHM applications through elaboration of: Standard terminology. Definition of standard objectives of AE SHM. Definition of typical AE SHM process. Theoretical axioms/postulates of the AE SHM. Motivation for SHM : Motivation for SHM SHM is emerging engineering field that is driven by two main motivations: Safety and increasing performance. Commercial motivation and basis for condition-based maintenance. Structural Health Monitoring – Terms and Definitions : Structural Health Monitoring – Terms and Definitions Structural health monitoring is a process of diagnosis and monitoring condition of structures normally performed during their operation. Diagnosis is a process of detection, identification and assessment of flaws, properties or conditions that affect or may affect in future safety/performance of a structure. Diagnostic AE - is an acoustic emission methodology capable to achieve goals of diagnosis. Monitoring - a process of follow-up over changes in the condition of a structure. Flaw – an imperfection or discontinuity that may be detectable by nondestructive testing and is not necessarily rejectable [ASTM E1316]. Fault - an abnormal condition or defect at the component, equipment, or sub-system level which may lead to a failure [ISO/CD 10303-226]. Prediction – a process of estimation of possible future flaw/fault deterioration based on results of diagnostics, monitoring and/or numerical modeling. Structural health monitoring combines elements of non-destructive testing, condition/process monitoring, statistical pattern recognition and physical modeling. Five Objectives of SHM : Five Objectives of SHM Structural Health Monitoring vs. Non-Destructive Testing : Structural Health Monitoring vs. Non-Destructive Testing Structural health monitoring is applied non-destructively and in many cases incorporates different NDT methods. Nevertheless, there are several conceptual differences between both approaches: Usually, the primary goals of NDE in industrial applications are limited to detection and evaluation of flaws' geometry and orientation. Flaw assessment and remaining lifetime evaluation usually are not considered goals of NDE and performed separately if at all. Traditional NDE methods cannot be applied during operation and inappropriate for continues monitoring. AE and SHM : AE and SHM Acoustic emission method fits uniquely to the concept of structural health monitoring due to multiple phenomenological advantages. Particularly, it can be used for: Diagnostics of overall structural integrity including detection, location, identification and assessment of flaws/faults during normal operation of a structure. Continuous or periodic monitoring. Identification of operation conditions that cause flaw/faults origination and development. Process of SHM : Process of SHM Procedure Development : Procedure Development Development of new AE SHM applications is essentially based on a learning process. This includes collection and analysis of information about: Material properties. Structural design, history of operation, repairs and results of previous inspections. Applied loads, operational and environmental conditions. Typical flaws/faults to be detected, assessed and monitored. AE characteristics of flaws/faults to be detected, assessed and monitored. Wave propagation characteristics in the material and geometry of the inspected structure including propagation modes, attenuation, dispersion, scattering and other characteristics. AE instrumentation appropriate for the particular application. Sensing : Sensing Sensing is a process of data measurement. It involves measurement of AE as well as parametric data like pressure, temperature, strain and other according to the developed SHM procedure. There are several important aspects to address during the sensing stage. First, it is important check that data collected during data acquisition process is valid and can be satisfactory used for the purposes defined in the developed SHM procedure. If this is not a case, additional measurements with different setup or loading, operational and/or environmental conditions may be required. Second, and the most important, it is an express evaluation of structure condition based on the measured data for major conditions that may threaten the structure immediately or in a short term. Diagnosis : Diagnosis Diagnosis is one of the primary goals of SHM. Diagnosis in SHM is a process of detection, identification and assessment of flaws/faults in a structure or system. To achieve these objectives special development efforts are required including material research, numerical modeling, and small or full scale samples tests. Numerical modeling, analysis of stress conditions, history of the inspected structure, local application of different NDE methods, material investigations and other may be required to crystallize the most correct diagnostic picture regarding the condition of an examined structure. Diagnosis (Greek: διάγνωση, from δια dia- "apart-split", and γνώση gnosi "to learn, knowledge") is the identification of the nature of anything, either by process of elimination or other analytical methods (Wikipedia). Diagnosis performed based on collected data using methods of statistical pattern recognition. Pattern recognition is a branch of artificial intelligence concerned with the classification or description of observations. Monitoring : Monitoring Monitoring is essential for evaluation: Flaw/fault development rate. Next repetitive inspection interval. Distinguishing between developing and non-developing flaws/faults. Monitoring performed periodically or continuously depending on the particular application. For success of monitoring it is necessary to identify during SHM procedure development quantitative and/or qualitative AE and other measured parameters' characteristics of flaws/faults that are changing with their development. It is important to performed monitoring under normal operational and environmental conditions of a structure. If a change in stress/operational/environmental conditions occurs from any reason or a structure has been subjected to extreme influence and trauma, it may require change in monitoring policy. Prediction : Prediction The goals of prediction are to: Identify the useful a remaining lifetime of a component or structure. Define an appropriate re-inspection/monitoring policy based on diagnostic and monitoring data. Provide information necessary for CBM decisions. Prediction normally done based on diagnostic results, several monitoring and in conjunction with all information about the structure, its history and all know measurable or not risk factors. Fundamental Assumptions and Principals of AE SHM : Fundamental Assumptions and Principals of AE SHM Structural health monitoring by the AE method as any other scientific concept is based on a set of fundamental assumptions that are normally self-evident and not necessary have to be scientifically proven. The role of assumptions is to define a systematic basis of a concept or theory. Four groups of fundamental assumptions: SHM procedure development. Structure diagnosis and monitoring. Data analysis. Prediction and recommendations. Assumption Group 1 – AE SHM Procedure Development : Assumption Group 1 – AE SHM Procedure Development An optimal SHM procedure is one that ensures a maximum probability of flaw/fault detection while minimizing false negative findings. Development of new AE SHM applications is essentially based on a learning process. This includes collection and analysis of information about: Structural design, history of operation, repairs and results of previous inspections. Material properties. Applied loads, operational and environmental conditions. Typical flaws/faults that can develop in the inspected structure. AE characteristics of flaws/faults to be detected, assessed and monitored. Wave propagation characteristics in the material and geometry of the inspected structure including propagation modes, attenuation, dispersion, scattering and other characteristics. AE instrumentation appropriate for the particular application. An optimal loading and/or environmental conditions for performing SHM are considered those under which flaws/faults naturally originate and develop in the inspected structure. Assumption Group 2 – Structural Diagnosis and Monitoring : Assumption Group 2 – Structural Diagnosis and Monitoring A specific AE methodology can be considered diagnostic if essentially it allows: Detection. Location. Identification. Assessment (qualitatively or quantitatively) of flaws/faults in the inspected structure. Acoustic emission is flaw/fault-stage-material specific, i.e. different flaws and faults at different stages of their development in different materials have different AE characteristics. Flaw/fault identification (typification) and assessment in AE SHM is possible when unique AE characteristics or AE fingerprints characterizing different flaws/faults at different stages of their development in the specific material can be identified, effectively distinguished and compared with similar characteristics obtained in similar applications or in laboratory tests with known flaws/faults at known stage. During flaw/fault assessment, a conservative approach should be taken in case of uncertain results. Flaws/faults that can be equally classified into two different groups by their severity level should be attributed to the group corresponding to more severe flaws/faults. Comparison of loading, operational and/or environmental conditions with AE activity or AE characteristics reflecting kinetic characteristics of flaws/faults development can be used to identify conditions causing flaw/fault origination, development, acceleration or arrest. Flaw/fault monitoring is possible when quantitative and/or qualitative AE characteristics changing with flaw/fault development are identified. Reliable monitoring and prediction is possible when there are no changes in the stress and/or environmental conditions through the monitoring period. Assumption Group 3 – Data analysis : Assumption Group 3 – Data analysis The process of data analysis in AE SHM necessary includes the following steps: Analog and/or digital signal filtering. Initial feature extraction. Feature selection and dimension reduction. Clustering (unsupervised classification) and/or discrimination (supervised classification). Interpretation. Detection of AE activity suspected to flaw/fault development is a problem of statistical outlier detection. Signal's features selected for data analysis should be a minimum set of statistically significant features necessary for the specific SHM application; filtered and normalized whenever is required so influence of background noise is minimized and data measured at different times and different locations is comparable. Features used in data analysis should have established relationship with physical phenomena being measured during AE SHM in order insure correct diagnosis of the inspected structure. AE activity distinguishable from AE background noise should be considered as flaw/fault related activity unless different is proven. All detected AE activity distinguishable from AE background noise should be analyzed regardless if it is locatable or not. Flaw/fault detection and location typically can be done using unsupervised methods while identification and assessment by supervised methods of statistical patter recognition. Assumption Group 4 – Prediction and Recommendations : Assumption Group 4 – Prediction and Recommendations A non-developing flaw/fault cannot cause a failure unless there is a change in loading, operational and/or environmental conditions. Optimal re-inspection interval is such that a risk of unexpected failure is reduced to the minimum acceptable probability, defined for the specific application. Remaining life-time of the inspected structure can be evaluated when a law of flaw/fault development is established using monitoring data and/or numerical modeling. Conclusions : Conclusions In this work, the fundamental principles of the structural health monitoring by the Acoustic Emission method were elaborated and discussed. This includes terminology, standard process of AE SHM and fundamental assumptions. The proposed fundamentals can be used for systematic development of new AE SHM procedures and applications. More information at:Muravin.com : More information at:Muravin.com You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.