scholarly journals Novel Damage Detection Techniques for Structural Health Monitoring Using a Hybrid Sensor

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Dengjiang Wang ◽  
Jingjing He ◽  
Banglin Dong ◽  
Xiaopeng Liu ◽  
Weifang Zhang
Keyword(s):  
Damage Detection ◽  
Fatigue Testing ◽  
Fatigue Cracks ◽  
Probability Of Detection ◽  
Model Parameters ◽  
The Novel ◽  
Plate Structures ◽  
Experimental Procedure ◽  
Detection Techniques ◽  
Sensor Monitoring

This study presents a technique for detecting fatigue cracks based on a hybrid sensor monitoring system consisting of a combination of intelligent coating monitoring (ICM) and piezoelectric transducer (PZT) sensors. An experimental procedure using this hybrid sensor system was designed to monitor the cracks generated by fatigue testing in plate structures. A probability of detection (POD) model that quantifies the reliability of damage detection for a specific sensor or the nondestructive testing (NDT) method was used to evaluate the weight factor for the ICM and PZT sensors. To estimate the uncertainty of model parameters in this study, the Bayesian method was employed. Realistic data from fatigue testing was used to validate the overall method, and the results show that the novel damage detection technique using a hybrid sensor can quantify fatigue cracks more accurately than results obtained by conventional sensor methods.

Qualification of a Combined Ultrasonic Inspection Tool for Detection and Sizing of Circumferential Weld Cracks in Offshore Pipelines

2014 ◽  
Author(s):  
Herbert Willems ◽  
Hans Petter Bjørgen ◽  
Thor-Ståle Kristiansen ◽  
Guus Wieme
Keyword(s):  
Fatigue Testing ◽  
Fatigue Cracks ◽  
Ultrasonic Inspection ◽  
Probability Of Detection ◽  
Offshore Pipelines ◽  
Fast Screening ◽  
Standard Application ◽  
Weld Area ◽  
Pulse Echo ◽  
Non Destructive

The target of inline crack inspection is normally related to the detection of axial cracks (weld cracks, SCC etc.) as axial cracks are usually expected under typical loading conditions in pressurized pipe. Ultrasonic crack inspection tools for this type of cracks have been available for over 20 years and have become a standard application in the ILI business. However, under certain conditions circumferential cracking may occur and the inspection technique needs to be modified accordingly. Especially under offshore conditions with limited pipeline accessibility not only the early detection of crack-like defects is required but also a precise depth sizing is important in order to minimize the risk of crack-related pipeline failure. In order to ensure a high probability of detection together with state-of-the-art depth sizing, a 10″ inline inspection tool was developed for the detection of circumferentially orientated weld cracks. The tool combines the advantages of the pulse-echo technique on the detection side with the excellent capabilities of the TOFD (time-of-flight-diffraction) technique for accurate sizing. Both techniques are implemented into a tethered tool where the pulse-echo unit serves for fast screening while the relatively slow TOFD-unit is used for sizing of any detected crack-like features. In order to qualify the new tool for a special offshore application (inspection of circumferential cracking at welded anode pads) extensive testing was performed using a 10″ test pipeline prepared by Statoil. The test line contained 64 artificial weld defects for reference purposes as well as an unknown number of fatigue cracks in the weld area which were generated by fatigue testing of the corresponding pipes. The tests were full blind tests with no advance knowledge on locations and sizes of the cracks. The sizes of the fatigue cracks (length, depth) were determined by destructive examinations carried out after inline testing. The subsequent comparison of the destructive results with the non-destructive results showed that the specification of the tool with regard to detection and sizing was fully met. In the paper, the inspection concept and the setup of the new tool are described, and the results of the qualification tests are presented.

A Novel Probability of Detection Assessment Considering Model Uncertainty for Lamb Wave Detection

2021 ◽  
Author(s):  
Chenjun Gao ◽  
Jingjing He ◽  
Xuefei Guan
Keyword(s):  
Model Selection ◽  
Damage Detection ◽  
Lamb Wave ◽  
Bayes Factor ◽  
Choice Model ◽  
Assessment Method ◽  
Uncertain Variable ◽  
Probability Of Detection ◽  
Model Parameters ◽  
Model Selection Uncertainty

Abstract Uncertainty in Non-Destructive Evaluation (NDE) arises from many sources, e.g., manufacturing variability, environmental noise, and inadequate measurement devices. The reliability of the NDE measurements is typically quantified by the probability of detection (POD). With the advent and technical developments of the simulation method and computer science, efforts have been devoted to generating and estimating the POD curve for Lamb wave damage detection. However, few studies have been reported on the POD evaluation considering model selection uncertainty. This paper presents a novel POD assessment method incorporating model selection uncertainty for Lamb wave damage detection. By treating the flaw quantification model as a discrete uncertain variable, a hierarchical probabilistic model for Lamb wave POD is formulated in the Bayesian framework. Uncertainties from the model choice, model parameters, and other variables can be explicitly incorporated using the proposed method. The Bayes factor is used to evaluate the performance of models. The posterior distributions of model parameters and the model fusion results are calculated through the Bayesian update using the reversible jump Markov chain Monte Carlo method. A fatigue problem with naturally developed cracks is used to demonstrate the proposed method.

scholarly journals Analysis and Prediction of COVID-19 Using SIR, SEIQR, and Machine Learning Models: Australia, Italy, and UK Cases

Information ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 109 ◽  
Author(s):  
Iman Rahimi ◽  
Amir H. Gandomi ◽  
Panagiotis G. Asteris ◽  
Fang Chen
Keyword(s):  
Machine Learning ◽  
Logistic Function ◽  
Prediction Performance ◽  
Machine Learning Algorithms ◽  
Model Parameters ◽  
The Novel ◽  
Chinese City ◽  
Limited Memory ◽  
Increasing Trend ◽  
Novel Coronavirus

The novel coronavirus disease, also known as COVID-19, is a disease outbreak that was first identified in Wuhan, a Central Chinese city. In this report, a short analysis focusing on Australia, Italy, and UK is conducted. The analysis includes confirmed and recovered cases and deaths, the growth rate in Australia compared with that in Italy and UK, and the trend of the disease in different Australian regions. Mathematical approaches based on susceptible, infected, and recovered (SIR) cases and susceptible, exposed, infected, quarantined, and recovered (SEIQR) cases models are proposed to predict epidemiology in the above-mentioned countries. Since the performance of the classic forms of SIR and SEIQR depends on parameter settings, some optimization algorithms, namely Broyden–Fletcher–Goldfarb–Shanno (BFGS), conjugate gradients (CG), limited memory bound constrained BFGS (L-BFGS-B), and Nelder–Mead, are proposed to optimize the parameters and the predictive capabilities of the SIR and SEIQR models. The results of the optimized SIR and SEIQR models were compared with those of two well-known machine learning algorithms, i.e., the Prophet algorithm and logistic function. The results demonstrate the different behaviors of these algorithms in different countries as well as the better performance of the improved SIR and SEIQR models. Moreover, the Prophet algorithm was found to provide better prediction performance than the logistic function, as well as better prediction performance for Italy and UK cases than for Australian cases. Therefore, it seems that the Prophet algorithm is suitable for data with an increasing trend in the context of a pandemic. Optimization of SIR and SEIQR model parameters yielded a significant improvement in the prediction accuracy of the models. Despite the availability of several algorithms for trend predictions in this pandemic, there is no single algorithm that would be optimal for all cases.

Lifetime Enhancement of Propulsion Shafts Against Corrosion-Fatigue by Laser Peening

2018 ◽  
Author(s):  
Lloyd A. Hackel ◽  
Jon E. Rankin
Keyword(s):  
Corrosion Fatigue ◽  
Fatigue Testing ◽  
Salt Water ◽  
Fatigue Cracks ◽  
Water Immersion ◽  
High Energy ◽  
General Corrosion ◽  
Laser Peening ◽  
Corrosion Pits ◽  
Deep Pits

This paper reports substantially enhanced fatigue and corrosion-fatigue lifetimes of propulsion shaft materials, 23284A steel and 23284A steel with In625 weld overlay cladding, as a result of shot or laser peening. Glass reinforced plastic (GRP) coatings and Inconel claddings are used to protect shafts against general corrosion and corrosion pitting. However salt water leakage penetrating under a GRP can actually enhance pitting leading to crack initiation and growth. Fatigue coupons, untreated and with shot or laser peening were tested, including with simultaneous salt water immersion. Controlled corrosion of the surfaces was simulated with electric discharge machining (EDM) of deep pits enabling evaluation of fatigue and corrosion-fatigue lifetimes. Results specifically show high energy laser peening (HELP) to be a superior solution, improving corrosion-fatigue resistance of shaft and cladding metal, reducing the potential for corrosion pits to initiate fatigue cracks and dramatically slowing crack growth rates. At a heavy loading of 110% of the 23284A steel yield stress and with 0.020 inch deep pits, laser peening increased fatigue life of the steel by 1370% and by 350% in the corrosion-fatigue testing.

scholarly journals A Study on the Generalized Approximation Modeling Method Based on Fitting Sensitivity for Prediction of Engine Performance

2017 ◽  
Vol 2017 ◽  
pp. 1-12
Author(s):  
Lin Lin ◽  
Fang Wang ◽  
Shisheng Zhong
Keyword(s):  
Engine Performance ◽  
Grey Model ◽  
Model Parameters ◽  
Bayesian Regularization ◽  
Safety Engineering ◽  
The Novel ◽  
Mean Square ◽  
Approximation Model ◽  
Mean Square Errors ◽  
Fitting Accuracy

Prediction technology for aeroengine performance is significantly important in operational maintenance and safety engineering. In the prediction of engine performance, to address overfitting and underfitting problems with the approximation modeling technique, we derived a generalized approximation model that could be used to adjust fitting precision. Approximation precision was combined with fitting sensitivity to allow the model to obtain excellent fitting accuracy and generalization performance. Taking the Grey model (GM) as an example, we discussed the modeling approach of the novel GM based on fitting sensitivity, analyzed the setting methods and optimization range of model parameters, and solved the model by using a genetic algorithm. By investigating the effect of every model parameter on the prediction precision in experiments, we summarized the change regularities of the root-mean-square errors (RMSEs) varying with the model parameters in novel GM. Also, by analyzing the novel ANN and ANN with Bayesian regularization, it is concluded that the generalized approximation model based on fitting sensitivity can achieve a reasonable fitting degree and generalization ability.

scholarly journals A probabilistic method for structural integrity assurance based on damage detection structural health monitoring data

2021 ◽  
pp. 147592172110388
Author(s):  
Michael Siu Hey Leung ◽  
Joseph Corcoran
Keyword(s):  
Damage Detection ◽  
Particle Filtering ◽  
Structural Integrity ◽  
Probabilistic Method ◽  
Probability Of Detection ◽  
Monitoring Systems ◽  
Negative Results ◽  
Systematic Effects ◽  
Detection Capabilities ◽  
Integrity Assurance

The value of using permanently installed monitoring systems for managing the life of an engineering asset is determined by the confidence in its damage detection capabilities. A framework is proposed that integrates detection data from permanently installed monitoring systems with probabilistic structural integrity assessments. Probability of detection (POD) curves are used in combination with particle filtering methods to recursively update a distribution of postulated defect size given a series of negative results (i.e. no defects detected). The negative monitoring results continuously filter out possible cases of severe damage, which in turn updates the estimated probability of failure. An implementation of the particle filtering method that takes into account the effect of systematic uncertainty in the detection capabilities of a monitoring system is also proposed, addressing the problem of whether negative measurements are simply a consequence of defects occurring outside the sensors field of view. A simulated example of fatigue crack growth is used to demonstrate the proposed framework. The results demonstrate that permanently installed sensors with low susceptibility to systematic effects may be used to maintain confidence in fitness-for-service while relying on fewer inspections. The framework provides a method for using permanently installed sensors to achieve continuous assessments of fitness-for-service for improved integrity management.

Fatigue Testing of Large-Scale Models of Submarine Structural Details

1965 ◽  
Vol 2 (03) ◽  
pp. 299-307
Author(s):  
Frank W. Dunham
Keyword(s):  
Cyclic Loading ◽  
Large Scale ◽  
Fatigue Testing ◽  
Fatigue Cracks ◽  
Pressure Variation ◽  
Test Tank ◽  
Initiation And Propagation ◽  
Scale Models ◽  
Structural Details

The conversion of a 30-ft-dia test tank to a facility for subjecting large-scale models of submarine structural details to cyclic loading is described. By means of automatically controlled valves, models were subjected to a pressure variation simulating a submarine diving to its test depth and returning to the surface. The cyclic rate was slightly less than one per minute. The system was so designed that the test tank itself was not subjected to the pressure variations. Details of a series of models designed to simulate particular structural details of interest in recent submarine construction are described. Results of the tests to date are summarized, and several observations relative to the initiation and propagation of fatigue cracks in submarine structural details are presented.

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