[HTML][HTML] A comprehensive review on piezo impedance based multi sensing technique

L Parida, S Moharana - Results in Engineering, 2023 - Elsevier
In recent era of constructional practices, sensor-based Structural Health Monitoring (SHM) is
widely utilized and considered as a trustworthy Non-Destructive Evaluation (NDE) technique …

Deep learning for structural health monitoring: Data, algorithms, applications, challenges, and trends

J Jia, Y Li - Sensors, 2023 - mdpi.com
Environmental effects may lead to cracking, stiffness loss, brace damage, and other
damages in bridges, frame structures, buildings, etc. Structural Health Monitoring (SHM) …

Comparative assessment of a multitudinal piezo arrangement for non-destructive evaluation of construction steel: An experimental study

L Parida, S Moharana - Measurement, 2023 - Elsevier
Recently, sensor-based health diagnostic methods have attracted remarkable attention and
can be replaced with conventional nondestructive techniques due to their robustness …

Corrosion inhibitors for enhanced strength, durability, and microstructure of coastal concrete structures

S Subash, L Parida, U Singh… - Materials Research …, 2023 - iopscience.iop.org
The prevalence of catastrophic structural member failure caused by steel corrosion in civil
infrastructure underscores the importance of reducing reinforcement corrosion to enhance …

A proof of concept study on reliability assessment of different metal foil length based piezoelectric sensor for electromechanical impedance techniques

L Parida, S Moharana, R Vicente, G Ascensão - Scientific Reports, 2024 - nature.com
Lead zirconate titanate (PZT) patches gained popularity in structural health monitoring
(SHM) for its sensing and cost effective. However, a robust installation of PZT patches is …

A real-time remaining fatigue life prediction approach based on a hybrid deep learning network

Y Zhu, J Zhang, J Luo, X Guo, Z Liu, R Zhang - Processes, 2023 - mdpi.com
Fatigue failure is a typical failure mode of welded structures. It is of great engineering
significance to predict the remaining fatigue life of structures after a certain period of service …

Machine and Deep Learning Methods for Concrete Strength Prediction: A Bibliometric and Content Analysis Review of Research Trends and Future Directions

R Kumar, E Althaqafi, SGK Patro, V Simic… - Applied Soft …, 2024 - Elsevier
This review paper provides a detailed evaluation of the existing landscape and future trends
in applying machine learning and deep learning approaches for predicting concrete strength …

Using wavelet transform and hybrid CNN–LSTM models on VOC & ultrasound IoT sensor data for non-visual maize disease detection

TJ Maginga, E Masabo, P Bakunzibake, KS Kim… - Heliyon, 2024 - cell.com
Early detection of plant diseases is crucial for safeguarding crop yield, especially in regions
vulnerable to food insecurity, such as Sub-Saharan Africa. One of the significant contributors …

Machine learning approach for predicting impedance signatures of construction steel structures in various tensile pull actions

L Parida, S Moharana, SK Giri - Materials Today: Proceedings, 2023 - Elsevier
The detection of structural damage based on the electromechanical impedance technique is
proven to have a greater sensitivity to structures based on baseline impedance signature …

[HTML][HTML] Early detection of thermal instability in railway tracks using piezo-coupled structural signatures

T Banerjee, S Moharana, L Parida - Journal of Infrastructure Intelligence …, 2023 - Elsevier
Rail accidents caused by rail track derailments have been a growing concern due to
repetitive thermal changes resulting from high temperature stresses in rails due to rail …