An automated hypersphere-based healthy subspace method for robust and unsupervised damage detection via random vibration response signals

2021 ◽  
pp. 147592172110044
Author(s):  
Vamvoudakis-Stefanou Kyriakos ◽  
Fassois Spilios ◽  
Sakellariou John
Keyword(s):  
Damage Detection ◽  
High Performance ◽  
Random Vibration ◽  
Feature Space ◽  
Vibration Response ◽  
Alternative Methods ◽  
Detection Methods ◽  
Subspace Method ◽  
Uncertainty Sources ◽  
Automated Algorithm

A novel, unsupervised, hypersphere-based healthy subspace method for robust damage detection under non-quantifiable uncertainty via a limited number of random vibration response sensors is postulated. The method is based on the approximate construction, within a proper feature space, of a healthy subspace representing the healthy structural dynamics under uncertainty as the union of properly selected hyperspheres. This is achieved via a fully automated algorithm eliminating user intervention, and thus subjective selections, or complex optimization procedures. The main asset of the proposed method lies in combining simplicity and full automation with high performance. Its performance is systematically assessed via two experimental case studies featuring various uncertainty sources and distinct healthy subspace geometries, while interesting comparisons with three well-known robust damage detection methods are also performed. The results indicate excellent detection performance, which also compares favorably to that of alternative methods.

Plate Damage Detection Using Vibration-Based and Static Deformation-Based Approaches

2011 ◽  
Author(s):  
Jing Shi ◽  
X. W. Tangpong
Keyword(s):  
Fractal Dimension ◽  
Damage Detection ◽  
Vibration Response ◽  
Static Deformation ◽  
Detection Methods ◽  
Mode Shapes ◽  
Response Data ◽  
Element Simulation ◽  
Catastrophic Failures ◽  
Aluminum Plates

Damage detection is important for sensing and analyzing the degradation of structures, and can effectively avoid potential catastrophic failures. Among the numerous studies in literature, most emphasis was given to the damage detection based on vibration response signals for simple beam structures. In this paper, the feasibility of roughness method for plates was investigated using both vibration-based data and static deformation data. Two detection methods, namely, roughness method and fractal dimension method, were used to analyze the data. Both types of data were obtained for aluminum plates using finite element simulation. It was found that both methods were able to detect the damage and locate its position precisely with the two types of signals. The effectiveness of damage detection using static deformation data was further demonstrated by experimenting with a cracked cantilever beam. A computer vision camera efficiently and automatically collected the static deformation data, and this approach showed great potential compared with the expensive and time-consuming collection process for vibration response data such as mode shapes.

Elimination of outlier measurements for damage detection of structures under changing environmental conditions

2021 ◽  
pp. 147592172199847
Author(s):  
William Soo Lon Wah ◽  
Yining Xia
Keyword(s):  
Damage Detection ◽  
Multiple Regression ◽  
Natural Frequencies ◽  
Detection Method ◽  
Detection Methods ◽  
Structure Model ◽  
Bridge Structure ◽  
Beam Structure ◽  
Dependent Variables ◽  
The Difference

Damage detection methods developed in the literature are affected by the presence of outlier measurements. These measurements can prevent small levels of damage to be detected. Therefore, a method to eliminate the effects of outlier measurements is proposed in this article. The method uses the difference in fits to examine how deleting an observation affects the predicted value of a model. This allows the observations that have a large influence on the model created, to be identified. These observations are the outlier measurements and they are eliminated from the database before the application of damage detection methods. Eliminating the outliers before the application of damage detection methods allows the normal procedures to detect damage, to be implemented. A multiple-regression-based damage detection method, which uses the natural frequencies as both the independent and dependent variables, is also developed in this article. A beam structure model and an experimental wooden bridge structure are analysed using the multiple-regression-based damage detection method with and without the application of the method proposed to eliminate the effects of outliers. The results obtained demonstrate that smaller levels of damage can be detected when the effects of outlier measurements are eliminated using the method proposed in this article.

scholarly journals Comparison of Novelty Detection Methods for Detection of Various Rotary Machinery Faults

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3536
Author(s):  
Jakub Górski ◽  
Adam Jabłoński ◽  
Mateusz Heesch ◽  
Michał Dziendzikowski ◽  
Ziemowit Dworakowski
Keyword(s):  
Novelty Detection ◽  
Feature Space ◽  
Detection Methods ◽  
Data Sets ◽  
Similar Distribution ◽  
Detection Algorithms ◽  
Rotary Machinery ◽  
Detection Approach ◽  
Input Reconstruction ◽  
Quantitative Indicators

Condition monitoring is an indispensable element related to the operation of rotating machinery. In this article, the monitoring system for the parallel gearbox was proposed. The novelty detection approach is used to develop the condition assessment support system, which requires data collection for a healthy structure. The measured signals were processed to extract quantitative indicators sensitive to the type of damage occurring in this type of structure. The indicator’s values were used for the development of four different novelty detection algorithms. Presented novelty detection models operate on three principles: feature space distance, probability distribution, and input reconstruction. One of the distance-based models is adaptive, adjusting to new data flowing in the form of a stream. The authors test the developed algorithms on experimental and simulation data with a similar distribution, using the training set consisting mainly of samples generated by the simulator. Presented in the article results demonstrate the effectiveness of the trained models on both data sets.

Analysis of vibration response and machining quality of hybrid robot based UD-CFRP trimming

2021 ◽  
pp. 095440542098609
Author(s):  
Yan Zhang ◽  
Hao Li ◽  
Xuda Qin ◽  
Jie liu ◽  
Zhuojie Hou
Keyword(s):  
High Performance ◽  
Vibration Response ◽  
Industrial Robots ◽  
Force Characteristic ◽  
Surface Waviness ◽  
Machined Surface ◽  
Machining Quality ◽  
3D Surface Roughness ◽  
Machined Surface Quality ◽  
Vibration Responses

To fulfill the demands of higher precision, better quality, and more flexibility, the usage of high-performance industrial robots is rapidly increased in aerospace industry. Considering the anisotropic and inhomogeneous characteristics of composite materials, this study focuses mainly on dynamic response investigation of a newly designed hybrid robot (named as TriMule) in CFRP trimming process and its influence on the machined quality. First, combined with the cutting force characteristic, the vibration responses of tool center point (TCP) under the dynamic excitation were obtained. The influences of robotic TCP vibration on machined surface quality with different fiber orientations, including surface waviness, cavity, 3D surface roughness, and depth of affected zone, are first studied by comparing hybrid robot and machine tool. From experiment results, it can be concluded the proposed TCP vibration response model has sufficient prediction accuracy. Meanwhile, it is found that larger robotic vibration response is accompanied by higher surface waviness, bigger surface cavity, and greater affected zone. Results also showed that the fiber orientation and milling style are two essential factors that affect robot vibration and machining quality during CFRP trimming.

A Study on Structural System Identification and Damage Detection for Free Vibration Response Using the Wavelet Transform

2015 ◽  
Vol 752-753 ◽  
pp. 1029-1034
Author(s):  
Asnizah Sahekhaini ◽  
Pauziah Muhamad ◽  
Masayuki Kohiyama ◽  
Aminuddin Abu ◽  
Lee Kee Quen ◽  
...  
Keyword(s):  
Free Vibration ◽  
Damage Detection ◽  
Vibration Response ◽  
Structural System ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Complex Morlet Wavelet ◽  
Structural System Identification ◽  
Free Vibration Response ◽  
Energy Components

This paper presents a wavelet-based method of identification modal parameter and damage detection in a free vibration response. An algorithm for modal parameter identification and damage detection is purposed and complex Morlet wavelet is chosen as an analysis wavelet function. This paper only focuses on identification of natural frequencies of the structural system. The method utilizes both undamaged and damage experiment data of free vibration response of the truss structure system. Wavelet scalogram is utilizes for damage detection. The change of energy components for undamaged and damage structure is investigated from the plot of wavelet scalogram which corresponded to the detection of damage.

Development and Achievements of SSM Processes for High Performance Components

2016 ◽  
Vol 256 ◽  
pp. 319-327 ◽  
Author(s):  
Mario Rosso ◽  
Ildiko Peter ◽  
Ivano Gattelli
Keyword(s):  
Industrial Development ◽  
High Performance ◽  
Rear Axle ◽  
Research Work ◽  
Industrial Applications ◽  
Alternative Methods ◽  
Front Suspension ◽  
Large Numbers ◽  
Automotive Parts ◽  
High Level

During the last decades under the enthusiastic and competent guidance of Mr Chiarmetta SSM processes attained in Italy at Stampal Spa (Torino) an unquestionable high level of industrial development with the production of large numbers of high performance automotive parts, like variety of suspension support, engine suspension mounts, steering knuckle, front suspension wheel, arm and rear axle. Among the most highlighted findings SSM processes demonstrated their capability to reduce the existing gap between casting and forging, moreover during such a processes there are the opportunity to better control the defect level.Purpose of this paper is to highlight the research work and the SSM industrial production attained and developed by Mr G.L. Chiarmetta, as well as to give an overview concerning some alternative methods for the production of enhanced performance light alloys components for critical industrial applications and to present an analysis of a new rheocasting process suitable for the manufacturing of high performance industrial components.

Functional Coatings for Damage Detection in Aerospace Structures

2021 ◽  
Vol 22 (1) ◽  
pp. 95-103
Author(s):  
Agathe Demay ◽  
Johnathan Hernandez ◽  
Perla Latorre ◽  
Remelisa Esteves ◽  
Seetha Raghavan
Keyword(s):  
Damage Detection ◽  
High Performance ◽  
Structural Integrity ◽  
Alumina Nanoparticles ◽  
Functional Coatings ◽  
Aerospace Structures ◽  
Non Invasive ◽  
Damage Sensing ◽  
Composite Substrate ◽  
Open Hole

The future of aerospace structures is highly dependent on the advancement of reliable and high-performance materials, such as composite materials and metals. Innovation in high resolution non-invasive evaluation of these materials is needed for their qualification and monitoring for structural integrity. Aluminum oxide (or α-alumina) nanoparticles present photoluminescent properties that allow stress and damage sensing via photoluminescence piezospectroscopy. This work describes how these nanoparticles are added into a polymer matrix to create functional coatings that monitor the damage of the underlying composite or metallic substrates. Different volume fractions of α-alumina nanoparticles in the piezospectroscopic coatings were studied for determining the sensitivity of the coatings and successful damage detection was demonstrated for an open-hole tension composite substrate as well as 2024 aluminum tensile substrates with a subsurface notch.

scholarly journals Separating damage from environmental effects affecting civil structures for near real-time damage detection

2017 ◽  
Vol 17 (4) ◽  
pp. 850-868 ◽  
Author(s):  
William Soo Lon Wah ◽  
Yung-Tsang Chen ◽  
Gethin Wyn Roberts ◽  
Ahmed Elamin
Keyword(s):  
Damage Detection ◽  
Real Time ◽  
Environmental Effects ◽  
Environmental Conditions ◽  
Principal Component ◽  
Detection Methods ◽  
Real Time Monitoring ◽  
Civil Structures ◽  
Data Set ◽  
Wide Range

Analyzing changes in vibration properties (e.g. natural frequencies) of structures as a result of damage has been heavily used by researchers for damage detection of civil structures. These changes, however, are not only caused by damage of the structural components, but they are also affected by the varying environmental conditions the structures are faced with, such as the temperature change, which limits the use of most damage detection methods presented in the literature that did not account for these effects. In this article, a damage detection method capable of distinguishing between the effects of damage and of the changing environmental conditions affecting damage sensitivity features is proposed. This method eliminates the need to form the baseline of the undamaged structure using damage sensitivity features obtained from a wide range of environmental conditions, as conventionally has been done, and utilizes features from two extreme and opposite environmental conditions as baselines. To allow near real-time monitoring, subsequent measurements are added one at a time to the baseline to create new data sets. Principal component analysis is then introduced for processing each data set so that patterns can be extracted and damage can be distinguished from environmental effects. The proposed method is tested using a two-dimensional truss structure and validated using measurements from the Z24 Bridge which was monitored for nearly a year, with damage scenarios applied to it near the end of the monitoring period. The results demonstrate the robustness of the proposed method for damage detection under changing environmental conditions. The method also works despite the nonlinear effects produced by environmental conditions on damage sensitivity features. Moreover, since each measurement is allowed to be analyzed one at a time, near real-time monitoring is possible. Damage progression can also be given from the method which makes it advantageous for damage evolution monitoring.

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