Negative selection algorithm based methodology for online structural health monitoring

Barontini, Alberto; Masciotta, Maria Giovanna; Amado-Mendes, Paulo; Ramos, Luís F.; Lourénço, Paulo B.

doi:10.1016/j.engstruct.2020.111662

Cited by 11 publications

(9 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To this end, it is necessary to define a baseline or reference condition and employ a strategy for model development, considering that two suitable approaches exist [13] as follows: (i) data-driven and (ii) model-based. In data-driven approaches, the generated model only depends on the experimental output data over time and aims at explaining the time-dependent variation of one or more of these damage-sensitive features [14][15][16][17]. In model-based approaches, instead, the physical characteristics of the system (i.e., geometry and mechanical properties) are considered to develop a detailed numerical model of the structure (e.g., employing finite element modelling strategies), calibrated by matching the numerical with the experimental response [18][19][20][21].…”

Section: Preventive Conservation Paradigm: Advantages and Open Challe...mentioning

confidence: 99%

Implementation of a Condition Monitoring Strategy for the Monastery of Salzedas, Portugal: Challenges and Optimisation

2023

Self Cite

View full text Add to dashboard Cite

The implementation of condition monitoring for damage identification and the generation of a reliable digital twin are essential elements of preventive conservation. The application of this promising approach to Cultural Heritage (CH) sites is deemed truly beneficial, constituting a minimally invasive mitigation strategy and a cost-effective decision-making tool. In this light, the present work focuses on establishing an informative virtual model as a platform for the conservation of the monastery of Santa Maria de Salzedas, a CH building located in the north of Portugal. The platform is the first step towards the generation of the digital twin and is populated with existing documentation as well as new information collected within the scope of an inspection and diagnosis programme. At this stage, the virtual model encompasses the main cloister, whose structural condition and safety raised concerns in the past and required the implementation of urgent remedial measures. In the definition of a vibration-based condition monitoring strategy for the south wing of the cloister, five modes were identified by carrying out an extensive dynamic identification. Nonetheless, significant challenges emerged due to the low amplitude of the ambient-induced vibrations and the intrusiveness of the activities. To this end, a data-driven Optimal Sensor Placement (OSP) approach was followed, testing and comparing five heuristic methods to define a good trade-off between the number of sensors and the quality of the collected information. The results showed that these algorithms for OSP allow the selection of sensor locations with good signal strength.

show abstract

Section: Preventive Conservation Paradigm: Advantages and Open Challe...mentioning

confidence: 99%

Implementation of a Condition Monitoring Strategy for the Monastery of Salzedas, Portugal: Challenges and Optimisation

2023

Self Cite

View full text Add to dashboard Cite

show abstract

“…Besides, motivated by the immune system, a negative selection algorithm (NSA) combined with Euclidean distance was used to detect the anomalous structural state under varying temperatures. 120…”

Section: Outlier Analysismentioning

confidence: 99%

“…Dervilis et al 119 concluded that MSD, MCD, and MVEE can successfully filter environmental variations from structural frequencies of Z24 bridge and validated that MCD achieves better damage sensitivity than the MSD, while the MVEE outperforms previous two; similar to KCPA, these distance metric‐based methods can also be used in combination with kernel mapping technique for damage detection in the SHM field. Besides, motivated by the immune system, a negative selection algorithm (NSA) combined with Euclidean distance was used to detect the anomalous structural state under varying temperatures 120 …”

Section: Elimination Of Modal Variability Based On Output‐only Model ...mentioning

confidence: 99%

Eliminating environmental and operational effects on structural modal frequency: A comprehensive review

Wang

Yang

et al. 2022

Structural Contr & Hlth

View full text Add to dashboard Cite

Modal frequencies are widely used for vibration-based structural health monitoring (SHM) and for capturing the dynamics of a monitored structure to reveal possible failures. However, changing environmental and operational conditions (i.e., temperature, humidity, wind load, and traffic load) may submerge the modal variability induced by structural damage, thereby falsely identifying damage of interest. This paper presents a comprehensive summary review of SHM for the prediction of modal frequency and the elimination of environment-induced masking effects based on the data normalization method. The influence mechanisms of external variations on modal frequencies extensively reported in the literature are first described. Next, the research progress in predicting and eliminating the operational modal variability is reviewed emphatically; this progress can be primarily divided into an inputoutput method that focuses on the establishment of the relationship model between structural frequency and environmental conditions and an outputonly method that separates the embedded environmental variable-induced changes depending on whether the environmental measurements are measured. Finally, the conclusions and future studies are summarized and discussed. As an overview, the major contribution of this paper is to provide objective technical references for engineers and owners and to further evaluate structural safety conditions more effectively and in a timely manner.

show abstract

“…Among the algorithms for the improved self-representation, some methodologies able to deal with such a scalability problem have been identified [53][54][55]. One of them has been already applied by the authors in [9] to elaborate an enhanced version of NSA for the damage detection of a scaled masonry arch tested in laboratory conditions, pointing out the possible advantages offered by the proposed approach but also highlighting the need for further analyses on full-scale structures exposed to real environmental and operational conditions. The present research work provides a contribution to this latter point.…”

Section: Feature Selection Strategymentioning

confidence: 99%

“…The classifier is a function trained through a dataset from the reference state of the system. Among the algorithms suitable to address such problems, the authors have recently investigated the applicability of Negative Selection Algorithms (NSAs), developing a deterministic generation based version that analyses the evolution of pairs of features at the same time [7][8][9]. The feature selection strategy that will be described in Section 2 is tailored to this new version of the NSA and it is based on the pairwise correlation of structural properties between themselves and with non-structural factors.…”

Section: Introductionmentioning

confidence: 99%

Reducing the Training Samples for Damage Detection of Existing Buildings through Self-Space Approximation Techniques

Barontini

Masciotta

Amado-Mendes

et al. 2021

Sensors

Self Cite

View full text Add to dashboard Cite

Data-driven methodologies are among the most effective tools for damage detection of complex existing buildings, such as heritage structures. Indeed, the historical evolution and actual behaviour of these assets are often unknown, no physical models are available, and the assessment must be performed only based on the tracking of a set of damage-sensitive features. Selecting the most representative state indicators to monitor and sampling them with an adequate number of records are therefore essential tasks to guarantee the successful performance of the damage detection strategy. Despite their relevance, these aspects have been frequently taken for granted and little attention has been paid to them by the scientific community working in the field of Structural Health Monitoring. The present paper aims to fill this gap by proposing a multistep strategy to drive the selection of meaningful pairs of correlated features in order to support the damage detection as a one-class classification problem. Numerical methods to reduce the number of necessary acquisitions and estimate the performance of approximation techniques are also provided. The analyses carried out to test and validate the proposed strategy exploit a dense dataset collected during the long-term monitoring of an outstanding heritage structure, i.e., the Church of ‘Santa Maria de Belém’ in Lisbon.

show abstract

Negative selection algorithm based methodology for online structural health monitoring

Cited by 11 publications

References 19 publications

Implementation of a Condition Monitoring Strategy for the Monastery of Salzedas, Portugal: Challenges and Optimisation

Implementation of a Condition Monitoring Strategy for the Monastery of Salzedas, Portugal: Challenges and Optimisation

Eliminating environmental and operational effects on structural modal frequency: A comprehensive review

Reducing the Training Samples for Damage Detection of Existing Buildings through Self-Space Approximation Techniques

Contact Info

Product

Resources

About